Systems, devices, and methods related to the individualized calibration and/or manufacturing of medical devices

ABSTRACT

Systems, devices, kits, and methods are provided herein in the form of example embodiments that relate to calibration of medical devices. The medical devices can be sensors adapted to sense a biochemical attribute. The embodiments can be used to determine calibration information specific to an individual medical device. The embodiments can determine the calibration information by reference to one or more parameters obtained during manufacturing of the medical device. The embodiments can also determine the calibration information by reference to in vitro testing of the medical devices. The embodiments also apply to systems incorporating those medical devices in their use in the field. Also described are embodiments of modifications to surfaces of sensor substrates, such as through applied radiation and/or the creation of a well, to aid in the placement and/or sizing of a sensor element on the substrate.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/950,538, filed Sep. 22, 2022, which is a continuation of U.S. patentapplication Ser. No. 17/891,588, filed Aug. 19, 2022, which is acontinuation of U.S. patent application Ser. No. 17/543,633, filed Dec.6, 2021, which is a continuation of U.S. patent application Ser. No.17/306,833, filed May 3, 2021, now U.S. Pat. No. 11,191,463, which is acontinuation of U.S. patent application Ser. No. 15/999,212, filed Aug.17, 2018, now U.S. Pat. No. 10,993,646, which claims the benefit of andpriority to U.S. Provisional Patent Application Ser. No. 62/547,635,filed Aug. 18, 2017, all of which are incorporated by reference hereinin their entireties and for all purposes.

FIELD

The subject matter described herein relates generally to systems,devices, and methods for determining or utilizing calibrationinformation specific to individual medical devices such as physiologicalsensors, and/or the manufacturing of physiological sensors.

BACKGROUND

A vast and growing market exists for monitoring the health and conditionof humans and other living animals. Information that describes thephysical or physiological condition of the human can be used incountless ways to assist and improve quality of life and diagnose andtreat undesirable human conditions.

A common device used to collect such information is a physiologicalsensor such as a biochemical sensor, or a device capable of sensing achemical attribute of a biological entity. Biochemical sensors come inmany forms and can be used to sense attributes in fluids, tissues, orgases forming part of or produced by a biological entity, such as ahuman being. These biochemical sensors can be used on or within the bodyitself, or they can be used on biological substances that have alreadybeen removed from the body.

The performance of a biochemical sensor can be characterized in a numberof ways, and a characteristic of particular importance can be theaccuracy of a biochemical sensor, or the degree to which the biochemicalsensor correctly measures the concentration or content of the chemicalbeing measured. The precision of the biochemical sensor, or the degreeto which the measured value is exact or refined, can also be important.

Although biochemical sensors often have a complex and well-studieddesign, they can still be subject to a degree of performance variation.This can be caused by a number of factors, including variations in themanufacturing process and variations in the constituent materials usedto fabricate the sensors. These variations can cause sensors of the samedesign and manufacturing process to have measurable differences in theirperformance. For these and other reasons, needs exist to improve theperformance of manufactured biochemical sensors.

SUMMARY

A number of example embodiments are provided herein that can be used toimprove the performance of medical devices such as biochemical sensors,as well as the devices and systems utilizing these sensors. Theseexample embodiments relate to improved techniques for assessing andpredicting the performance of biochemical sensors when put to use bypatients, healthcare professionals (HCPs), or other users. Many of theseexample embodiments pertain to the determination of calibrationinformation based on parameters measured, recorded, or otherwiseobtained during the manufacturing process. These parameters can beindividualized, or specific to a discrete sensor, and the calibrationinformation determined therefrom can likewise be individualized, orspecific to that discrete sensor.

In many example embodiments, the calibration information is determinedby also taking reference to actual tests of the sensing capability orcharacteristics of certain sensors. The data resulting from those testscan be used with the one or more parameters obtained during themanufacturing process to determine, estimate, extrapolate, or otherwisepredict the performance of the sensor once distributed to the user. Thetests, e.g., in vitro tests, used to assess sensing characteristics areoften destructive, contaminatory, or otherwise of a nature that renderthe tested sensor unsuitable for distribution to the user. In a numberof embodiments, the tests are performed on one or more sensors and theresults obtained therefrom are used with the manufacturing parameter ofa different, untested sensor to predict the performance of that untestedsensor. In this way, the performance of a particular sensor can bepredicted without subjecting the sensor to an in vitro test.

The information that represents the predicted performance of the sensorcan be embodied as calibration information, and this calibrationinformation can be made available to any device that seeks to use thesensing signal or data produced by the biochemical sensor to determinethe end result of the measurement, e.g., the concentration or content ofthe substance being sensed. While applicable to smaller scales, theembodiments described herein are particularly useful when applied tohigh-volume manufacturing processes. For example, the embodimentsdescribed herein can be applied to groups or batches of sensors that aremanufactured together. For example, in certain embodiments a subset ofone or more sensors from that group or batch are subjected to in vitrotesting, and the resulting test data is used with one or moremanufacturing parameters obtained from a different subset of sensors ofthe same group or batch to predict the performance of that differentsubset of sensors when distributed to users. Other example embodimentsare also described that incorporate one or more of the aspects describedhere, as well as other example embodiments that differ from thatdescribed here.

Also provided herein are a number of example embodiments of systems,devices, and methods for modifying a surface of a sensor substrate toaid in placement and/or sizing of a sensor element. In some of theseembodiments, an area of a surface of a sensor substrate can be modifiedwith electromagnetic radiation to create a modified area. The modifiedarea can have a surface characteristic that is changed such that themobility of a liquid applied to the substrate surface is eitherincreased or decreased by the modified area. Application of a liquid tothe surface of the sensor substrate can be performed such that theliquid comes to rest in a target area on the surface, where the targetarea is determined at least in part by the location of the modifiedarea. The electromagnetic radiation can take various forms, such aslaser radiation. In these and other embodiments, the surfacemodification can be the creation of a well in which a sensing elementcan be placed. The well can be created in various ways, such as byapplication of a mechanical force. Example embodiments of sensorsmanufactured with modified areas and/or wells are within the scope ofthis disclosure, as are devices, systems, and kits incorporating thesame.

Other systems, devices, methods, features, and advantages of the subjectmatter described herein will be or will become apparent to one withskill in the art upon examination of the following figures and detaileddescription. It is intended that all such additional systems, methods,features, and advantages be included within this description, be withinthe scope of the subject matter described herein, and be protected bythe accompanying claims. In no way should the features of the exampleembodiments be construed as limiting the appended claims, absent expressrecitation of those features in the claims.

BRIEF DESCRIPTION OF FIGURES

The details of the subject matter set forth herein, both as to itsstructure and operation, may be apparent by study of the accompanyingfigures, in which like reference numerals refer to like parts. Thecomponents in the figures are not necessarily to scale, emphasis insteadbeing placed upon illustrating the principles of the subject matter.Moreover, all illustrations are intended to convey concepts, whererelative sizes, shapes and other detailed attributes may be illustratedschematically rather than literally or precisely.

FIG. 1 is a block diagram depicting an example embodiment of an in vivoanalyte monitoring system.

FIG. 2 is a block diagram depicting an example embodiment of a dataprocessing unit.

FIG. 3 is a block diagram depicting an example embodiment of a displaydevice.

FIG. 4 as a schematic diagram depicting an example embodiment of ananalyte sensor.

FIG. 5A is a perspective view depicting an example embodiment of ananalyte sensor penetrating through the skin.

FIG. 5B is a cross sectional view depicting a portion of the analytesensor of FIG. 5A.

FIGS. 6-9 are cross-sectional views depicting example embodiments ofanalyte sensors.

FIG. 10A is a cross-sectional view depicting an example embodiment of ananalyte sensor.

FIGS. 10B-10C are cross-sectional views depicting example embodiments ofanalyte sensors as viewed from line A-A of FIG. 10A.

FIG. 11 is a conceptual view depicting an example embodiment of ananalyte monitoring system.

FIG. 12 is a block diagram depicting an example embodiment of on bodyelectronics.

FIG. 13 is a block diagram depicting an example embodiment of a displaydevice.

FIG. 14 is a flow diagram depicting an example embodiment of informationexchange within and analyte monitoring system.

FIGS. 15A, 15B, and 16 are top down views depicting example embodimentsof in vitro analyte sensors.

FIG. 17 is an exploded view depicting an example embodiment of an invitro analyte sensor.

FIG. 18A is a perspective view depicting an example embodiment of an invitro analyte meter.

FIG. 18B is a frontal view depicting an example embodiment of an invitro analyte meter.

FIG. 19A is a graph depicting an example of an in vitro sensitivity ofan analyte sensor.

FIG. 19B is a graph depicting examples of different sensitivities foranalyte sensors.

FIGS. 20A-20C are flow diagrams depicting example embodiments of methodsfor calibrating a medical device capable of sensing a biomedicalattribute.

FIG. 21A is a top down view depicting an example embodiment of a portionof an analyte sensor.

FIGS. 21B-21C are cross-sectional views depicting example embodiments ofa portion of an analyte sensor as viewed along line 21BC-21BC of FIG.21A.

FIG. 22A is a top down view depicting an example embodiment of a portionof an analyte sensor.

FIGS. 22B-22C are cross-sectional views depicting example embodiments ofa portion of an analyte sensor as viewed along line 22BC-22BC of FIG.22A.

FIG. 23A is a perspective view depicting an example embodiment of aportion of an analyte sensor.

FIG. 23B is a cross-sectional view depicting an example embodiment of aportion of an analyte sensor taken along line 23B-23B of FIG. 23A.

FIG. 24 is a cross-sectional view depicting an example embodiment of anin vivo sensor.

FIG. 25A is a perspective view depicting an example embodiment of ananalyte sensor.

FIG. 25B is a cross-sectional view depicting an example embodiment of ananalyte sensor taken along line 25B-25B of FIG. 25A.

FIG. 26A is an example plot of in vitro test data.

FIG. 26B is an example plot of sensitivities corresponding to the invitro test data of FIG. 26A.

FIGS. 27A-27F are flow diagrams depicting example embodiments of methodsof determining individualized calibration information.

FIGS. 28A-28B are flow diagrams depicting additional example embodimentsof methods related to determining individualized calibrationinformation.

FIG. 29A is a block diagram depicting an example embodiment of acomputer system that can be used to implement the calibrationembodiments described herein.

FIGS. 29B-29D are block diagrams depicting conceptual process andinformation flows with respect to the manufacturing of biochemicalsensors.

FIGS. 30A-30B are plots depicting example data sets demonstratingstatistically significant associations between in vivo sensitivity andcertain manufacturing parameters.

FIGS. 31A-31B are plots depicting sample data sets used in evaluatingcertain example embodiments.

FIGS. 32A-32F are schematic views depicting example embodiments of asensor substrate at various stages of manufacturing.

FIGS. 33A-B are top down photographs depicting example embodiments ofsensor substrates.

FIGS. 34A-34B are top down photographs depicting example embodiments ofsensing elements formed on sensor substrates.

FIGS. 35A-35D are schematic views depicting example embodiments ofmodified areas on sensor substrates.

FIGS. 36A-36B are flow diagrams depicting example embodiments of methodsof manufacturing one or more sensing elements.

FIGS. 37A-37B are schematic views depicting an example embodiment of asensor substrate at various stages of manufacturing.

FIG. 37C is a cross-section taken along line 37C-37C of FIG. 37B.

FIGS. 37D-F are cross-sections of additional example embodiments of asensor substrate.

FIG. 37G is a top down schematic view of an example embodiment of asensor substrate.

FIG. 37H is a cross-section taken along line 37H-37H of FIG. 37G.

FIGS. 38A-38D are cross-sections of example embodiments of a sensorsubstrate with electrochemical agents deposited thereon.

FIGS. 39A-39B are photographs depicting an example embodiment of atamping instrument.

FIGS. 40A-40B are photographs depicting example embodiments of sensorsubstrates having a well therein.

FIGS. 41A and 41B are top down photographs depicting an exampleembodiment of a well in a sensor substrate before and after agentdispersion.

FIGS. 42A and 42B are top down photographs depicting an exampleembodiment of a well in a sensor substrate before and after agentdispersion.

FIG. 43 is a series of top down photographs depicting various examplesof agent dispersion on sensor substrates with and without wells.

FIGS. 44A-44B are flow diagrams depicting example embodiments of methodsof manufacturing one or more sensing elements.

DETAILED DESCRIPTION

The present subject matter is described in detail with reference toexample embodiments. These example embodiments are set forth forillustrative purposes to aid those of ordinary skill in the art inunderstanding and appreciating the full scope of the present subjectmatter. These example embodiments do not constitute an exhaustiverecitation of all manners in which the present subject matter can beimplemented, as such an exhaustive recitation is both burdensome andunnecessary in light of the example embodiments explicitly set forth. Assuch, the present subject matter is of a breadth that extends beyondthose particular embodiments explicitly set forth herein.

The subject matter described herein generally relates to advancements intechniques for calibrating medical devices capable of sensing one ormore biochemical attributes, as well as systems and devices forperforming these calibration techniques. In many embodiments, thetechniques permit the determination of individualized calibrationinformation that varies between and is particular to individual medicaldevices, as opposed to a single calibration value that is determined forgroups of medical devices as a whole. There are many classes of medicaldevices that sense biochemical attributes, and thus there are manyapplications with which this subject matter can be utilized. Several ofthese classes of medical devices will be described herein, but these aremerely examples and do not constitute an exhaustive recitation of allclasses of medical devices with which the present subject matter findsutility.

Medical devices capable of sensing or monitoring chemical levels inbodily fluids can often be classified as part of either in vivo systemsor in vitro systems. In vivo systems include one or more medical devicesthat sense one or more biochemical attributes of bodily fluid that iswithin the human body, often by partially or wholly implanting themedical device (e.g., a sensor) within the human body. A common exampleis an in vivo analyte sensor useful in monitoring analyte levels in thehuman body. These analyte sensors can be designed to detect glucose orother analytes that are particularly relevant in monitoring a diabeticcondition.

In vitro systems include one or more medical devices that sense one ormore biochemical attributes of bodily fluid, such as blood, plasma,urine, etc., that has been removed from the human body, or othersubstances such as a homogenized biopsy sample. In vitro systems canalso be referred to as ex vivo systems. A common example is an in vitroanalyte sensor such as a test strip. In vitro test strips can also bedesigned to detect and measure glucose or other analytes that areparticularly relevant for monitoring a diabetic condition.

Systems and devices incorporating or utilizing data from either in vivoor in vitro medical devices are broadly referred to herein asbiochemical monitoring systems and biochemical monitoring devices,respectively. Systems and devices incorporating or utilizing data frommedical devices that are designed to sense the level of an analyte(e.g., glucose) are referred to herein as analyte monitoring systems andanalyte monitoring devices, respectively.

Example embodiments relating to these calibration techniques will bepresented by reference to their application to in vivo medical devicesand in vitro medical devices. The majority of the embodiments aredescribed with respect to in vivo medical devices, particularly, in vivoanalyte sensors. This is merely to facilitate the presentation of thefeatures and aspects of these example embodiments, and is not intendedto limit these calibration techniques to use with only in vivo analytesensors. Indeed, as noted already, the present subject matter is broadlyapplicable to other types of medical devices, a number of embodiments ofwhich will also be explicitly described.

Certain example embodiments relating to these calibration techniquespermit the determination of individualized calibration informationspecific to an individual sensor and, if desired, the subsequent use ofthat individualized calibration information to calibrate an output ofthe individual sensor. In many embodiments, the individualizedcalibration information is specific to each individual medical devicewithin a common manufacturing group or lot and can vary between eachindividual medical device with the common group. These embodiments arein contrast to approaches where a single calibration value is determinedfor a group or lot of medical devices as a whole such that every medicaldevice in the common manufacturing group has the same calibration value.

In some example embodiments, a sensing characteristic of a first subset(e.g., a sample or baseline subset) of medical devices is determined.For analyte sensors, this sensing characteristic can be, e.g., asensitivity of the sensor to the analyte. The sensing characteristic canbe determined with in vitro (or in vivo use) testing of the first subsetof medical devices. Examples of such testing will be described in moredetail herein. One or more individualized manufacturing parameter can bemeasured from each medical device in a different second subset ofmedical devices (e.g., a distribution subset intended for distributionfrom the manufacturer to third party users). In some exampleembodiments, the baseline and distribution subsets are taken from thesame production lot. The measurement of the individualized manufacturingparameter can be performed by, e.g., the manufacturer during or afterthe manufacturing process. The individualized manufacturing parametercan directly or indirectly correlate to the sensing characteristic ofthe medical device, and numerous examples of such individualizedmanufacturing parameters are described herein.

Individualized calibration information can then be independentlydetermined for each medical device within the distribution subset ofmedical devices using at least the individualized manufacturingparameter of each device within the distribution subset and the sensingcharacteristic of the baseline subset. This can result in calibrationinformation that is specific to each medical device in the distributionsubset and that can vary between the medical devices from variation ofthe individualized manufacturing parameter. In some embodiments, two ormore individualized manufacturing parameters are used to determine thecalibration information. In some embodiments, one or more qualitativemanufacturing parameters are used, either alone or in conjunction with aquantitative individualized manufacturing parameter.

As will be discussed in further detail herein, studies have confirmedthat embodiments of the present subject matter result in tangibleimprovements in the accuracy of biochemical sensing measurements made bythe medical devices. This represents an improvement in the operation ofthe calibrated medical devices themselves, which in turn results in animprovement in the operation of the monitoring systems and/or monitoringdevices incorporating these medical devices, as well as an improvementin the operation of the computing devices that process or otherwiseutilize the improved accuracy data produced by the calibrated medicaldevices. Improvements through lessening variations between medicaldevices were also confirmed, as were improvements to the manufacturingyield of the medical devices.

Before describing the embodiments relating to individualized calibrationtechniques in detail, it is first desirable to describe exampleembodiments of in vivo analyte monitoring systems and in vitro analytemonitoring systems, as well as examples of their operations, all ofwhich can be used with embodiments of these calibration techniques.

Example Embodiments of In Vivo Analyte Monitoring Systems

There are various types of analyte monitoring systems used with in vivosensors. “Continuous Analyte Monitoring” systems (e.g., “ContinuousGlucose Monitoring” systems), for example, are in vivo systems that cantransmit data from a sensor control device to a reader device repeatedlyor continuously without prompting, e.g., automatically according to aschedule. “Flash Analyte Monitoring” systems (e.g., “Flash GlucoseMonitoring” systems or simply “Flash” systems), as another example, arein vivo systems that can transfer data from a sensor control device inresponse to a scan or request for data by a reader device, such as witha Near Field Communication (NFC) or Radio Frequency Identification(RFID) protocol.

An in vivo analyte sensor can be partially or wholly implanted withinthe human body such that it makes contact with the bodily fluid in theuser and senses the analyte levels therein. The in vivo sensor can bepart of a sensor control device that resides on the body of the user andcontains the electronics and power supply that enable and control theanalyte sensing. The sensor control device, and variations thereof, canalso be referred to as a “sensor control unit,” an “on-body electronics”device or unit, an “on-body” device or unit, a “sensor datacommunication” device or unit, or a transmitter device or unit, to namea few. The term “on body” or “on-body” refers to any device that residesdirectly on the body or in close proximity to the body, such as awearable device (e.g., glasses, armband, wristband or bracelet,neckband, or necklace, etc.).

In vivo monitoring systems can also include one or more reader devicesthat receive sensed analyte data from the sensor control device. Thesereader devices can process, retransmit, and/or display the sensedanalyte data, in any number of forms. These devices, and variationsthereof, can be referred to as “handheld reader devices,” “readerdevices” (or simply, “readers”), “display devices,” “handheldelectronics” (or handhelds), “portable data processing” devices orunits, “data receivers,” “receiver” devices or units (or simplyreceivers), “relay” devices or units, “remote” devices or units,“companion” devices or units, “human interface” devices or units, toname a few. Computing devices such as personal computers can be used asa reader device.

In vivo analyte monitoring systems can be used with in vitro medicaldevices as well. For example, a reader device can incorporate or becoupled with a port for receiving an in vitro test strip carrying abodily fluid of the user, which can be analyzed to determine the user'sanalyte level.

In Vivo Sensors

In vivo sensors can be formed on a substrate, e.g., a substantiallyplanar substrate, or a non-planar rounded or cylindrical substrate. Inmany embodiments, the sensor comprises at least one electricallyconductive structure, e.g., an electrode. Sensor embodiments can besingle electrode embodiments (e.g., having no more than one electrode),or multiple electrode embodiments (e.g., having exactly two, exactlythree, or more electrodes). Embodiments of the sensor will often includea working electrode, and can also include at least one counter electrode(or counter/reference electrode), and/or at least one referenceelectrode (or at reference/counter electrode). Electrodes can bearranged as discrete regions electrically isolated by insulativeregions, and can be electrically connected to circuitry for receiving(and optionally conditioning and/or processing) the electrical signalsproduced by the electrodes. Electrodes can have planar (e.g., relativelyflat) surfaces or non-planar (e.g., relatively curved or rounded, suchas semi-hemispherical, cylindrical, or irregular surfaces andcombinations thereof). Electrodes can be arranged in layers orconcentrically or otherwise.

Accordingly, embodiments include analyte monitoring devices and systemsthat include an analyte sensor at least a portion of which ispositionable beneath the skin surface of the user for the in vivodetection of an analyte, including glucose, lactate, and the like, in abody fluid. Embodiments include wholly implantable analyte sensors andanalyte sensors in which only a portion of the sensor is positionedunder the skin and a portion of the sensor resides above the skin, e.g.,for contact to a sensor control device (which may include atransmitter), a receiver/display unit, transceiver, processor, etc. Thesensor may be, for example, positionable through an exterior skinsurface of a user for the continuous or periodic monitoring (periodicaccording to a regular interval, an irregular interval, a schedule,frequent repeats, etc.) of a level of an analyte in the user's bodilyfluid (e.g., interstitial fluid, subcutaneous fluid, dermal fluid,blood, or other bodily fluid of interest). For the purposes of thisdescription, continuous monitoring and periodic monitoring will be usedinterchangeably, unless noted otherwise. The sensor response may becorrelated and/or converted to analyte levels in blood or other fluids.In certain embodiments, an analyte sensor may be positioned in contactwith interstitial fluid to detect the level of glucose, which detectedglucose may be used to infer the glucose level in the user'sbloodstream. Analyte sensors may be insertable into a vein, artery, orother portion of the body containing fluid. Embodiments of the analytesensors may be configured for monitoring the level of the analyte over atime period which may range from seconds, minutes, hours, days, weeks,to months, or longer.

In certain embodiments, the analyte sensors, such as glucose sensors,are capable of in vivo detection of an analyte for one hour or more,e.g., a few hours or more, e.g., a few days or more, e.g., three or moredays, e.g., five days or more, e.g., seven days or more, e.g., severalweeks or more, or one month or more. Future analyte levels may bepredicted based on information obtained, e.g., the current analyte levelat time to, the rate of change of the analyte, etc. Predictive alarmsmay notify the user of predicted analyte levels that may be of concernin advance of the user's analyte level reaching the future predictedanalyte level. This provides the user an opportunity to take correctiveaction.

In an electrochemical embodiment, the sensor is placed,transcutaneously, for example, into a subcutaneous site such thatsubcutaneous fluid of the site comes into contact with the sensor. Inother in vivo embodiments, placement of at least a portion of the sensormay be in a blood vessel. The sensor operates to electrolyze an analyteof interest in the subcutaneous fluid or blood such that a current isgenerated between the working electrode and the counter electrode. Avalue for the current associated with the working electrode isdetermined. If multiple working electrodes are used, current values fromeach of the working electrodes may be determined. A microprocessor maybe used to collect these periodically determined current values or tofurther process these values.

If an analyte concentration is successfully determined, it may bedisplayed, stored, transmitted, and/or otherwise processed to provideuseful information. By way of example, raw signal or analyteconcentrations may be used as a basis for determining a rate of changein analyte concentration, which should not change at a rate greater thana predetermined threshold amount. If the rate of change of analyteconcentration exceeds the predefined threshold, an indication maybedisplayed or otherwise transmitted to indicate this fact. In certainembodiments, an alarm is activated to alert a user if the rate of changeof analyte concentration exceeds the predefined threshold.

As demonstrated herein, the present embodiments are useful in connectionwith a device that is used to measure or monitor an analyte (e.g.,glucose), such as any such device described herein. The embodimentsdescribed herein can be used to monitor and/or process informationregarding any number of one or more different analytes. Analytes thatmay be monitored include, but are not limited to, acetyl choline,amylase, bilirubin, carbon dioxide, cholesterol, chorionic gonadotropin,glycosylated hemoglobin (HbAlc), creatine kinase (e.g., CK-MB),creatine, creatinine, DNA, fructosamine, glucose, glucose derivatives,glutamine, growth hormones, hormones, ketones, ketone bodies, lactate,oxygen, peroxide, prostate-specific antigen, proteins, prothrombin, RNA,thyroid stimulating hormone, troponin, and any combination thereof. Theconcentration of drugs, such as, for example, antibiotics (e.g.,gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs ofabuse, theophylline, and warfarin, may be monitored in addition to orinstead of analytes. In embodiments that monitor more than one analyte,the analytes may be monitored at the same or different times. Thesemethods may also be used in connection with a device that is used tomeasure or monitor another analyte (e.g., ketones, ketone bodies, HbAlc,and the like), including oxygen, carbon dioxide, proteins, drugs, oranother moiety of interest, for example, or any combination thereof,found in bodily fluid, including subcutaneous fluid, dermal fluid,interstitial fluid, or other bodily fluid of interest, for example, orany combination thereof. In general, the device is in good contact, suchas thorough and substantially continuous contact, with the bodily fluid.

According to embodiments of the present disclosure, the measurementsensor is one suited for electrochemical measurement of analyteconcentration, for example glucose concentration, in a bodily fluid. Inthese embodiments, the measurement sensor includes at least a workingelectrode and a counter electrode. Other embodiments may further includea reference electrode. The working electrode is typically associatedwith a glucose-responsive enzyme. A mediator may also be included. Incertain embodiments, hydrogen peroxide, which may be characterized as amediator, is produced by a reaction of the sensor and may be used toinfer the concentration of glucose. In some embodiments, a mediator isadded to the sensor by a manufacturer, e.g., is included with the sensorprior to use. The redox mediator may be disposed relative to the workingelectrode and is capable of transferring electrons between a compoundand a working electrode, either directly or indirectly. The redoxmediator may be, for example, immobilized on the working electrode,e.g., entrapped on a surface or chemically bound to a surface.

Embodiments of the subject disclosure include in vivo analyte monitoringdevices, systems, kits, and processes of analyte monitoring and makinganalyte monitoring devices, systems, and kits. Included are on-body(e.g., at least a portion of a device, system or a component thereof ismaintained on the body of or in close proximity to a user to monitor ananalyte), physiological monitoring devices configured for real timemeasurement/monitoring of desired analyte level such as a glucose levelover one or more predetermined time periods such as one or morepredetermined monitoring time periods. Embodiments includetranscutaneously positioned analyte sensors that are electricallycoupled with electronics provided in a housing that is designed to beattached to the body of a user, for example, to a skin surface of auser, during the usage life of the analyte sensors or predeterminedmonitoring time periods. For example, on body electronics assemblyinclude electronics that are operatively coupled to an analyte sensorand provided in a housing for placement on the body of a user.

Such device and system with analyte sensors provide continuous orperiodic analyte level monitoring that is executed automatically, orsemi-automatically by control logic or routines programmed orprogrammable in the monitoring devices or systems. As used herein,continuous, automatic, and/or periodic monitoring refer to the in vivomonitoring or detection of analyte levels with transcutaneouslypositioned analyte sensors.

In certain embodiments, the results of the in vivo monitored analytelevel are automatically communicated from an electronics unit to anotherdevice or component of the system. That is, when the results areavailable, the results are automatically transmitted to a display device(or other user interaction device) of the system, for example, accordingto a fixed or dynamic data communication schedule executed by thesystem. In other embodiments, the results of the in vivo monitoredanalyte level are not automatically communicated, transferred, or outputto one or more device or component of the system. In such embodiments,the results are provided only in response to a query to the system. Thatis, the results are communicated to a component or a device of thesystem only in response to the query or request for such results. Incertain embodiments, the results of the in vivo monitoring may be loggedor stored in a memory of the system and only communicated or transferredto another device or component of the system after the one or morepredetermined monitoring time periods.

Embodiments include software and/or hardware to transform any one of thedevices, components, or systems into any one of the other devices,components, or systems, where such transformation may beuser-configurable after manufacture. Transformation modules that includehardware and/or software to accomplish such transformation may bemateable to a given system to transform it.

Embodiments include electronics coupled to analyte sensors that providefunctionalities to operate the analyte sensors for monitoring analytelevels over a predetermined monitoring time period such as for example,about 30 days (or more in certain embodiments), about 14 days, about 10,about 5 days, about 1 day, less than about 1 day. In certainembodiments, the usage life of each analyte sensor may be the same as ordifferent from the predetermined monitoring time periods. Components ofthe electronics to provide the functionalities to operate the analytesensors in certain embodiments include control logic or microprocessorscoupled to a power supply such as a battery to drive the in vivo analytesensors to perform electrochemical reactions to generate resultingsignals that correspond to the monitored analyte levels.

Electronics may also include other components such as one or more datastorage units or memory (volatile and/or non-volatile), communicationcomponent(s) to communicate information corresponding to the in vivomonitored analyte level to a display device automatically when theinformation is available, or selectively in response to a request forthe monitored analyte level information. Data communication betweendisplay devices and the electronics coupled to the sensor in certainembodiments are implemented serially (e.g., data transfer between themare not performed at the same time), or in parallel. For example, thedisplay device in certain embodiments is configured to transmit a signalor data packet to the electronics coupled to the sensor, and uponreceipt of the transmitted signal or data packet, the electronicscoupled to the sensor communicates back to the display device. Incertain embodiments, a display device may be configured to provide RFpower and data/signals continually, and detecting or receiving one ormore return data packet or signal from electronics coupled to the sensorwhen it is within a predetermined RF power range from the displaydevice. In certain embodiments, the display device and the electronicscoupled to the sensor may be configured to transmit one or more datapackets at the same time.

Embodiments also include electronics programmed to store or log in theone or more data storage units or a memory data associated with themonitored analyte level over the sensor usage life or during amonitoring time period. During the monitoring time period, informationcorresponding to the monitored analyte level may be stored but notdisplayed or output during the sensor usage life, and the stored datamay be later retrieved from memory at the end of the sensor usage lifeor after the expiration of the predetermined monitoring time period,e.g., for clinical analysis, therapy management, etc.

In certain embodiments, the predetermined monitoring time period is thesame as the sensor usage life time period such that when an analytesensor usage life expires (thus no longer used for in vivo analyte levelmonitoring), the predetermined monitoring time period ends. In certainembodiments, the predetermined monitoring time period may includemultiple sensor usage life time periods such that when an analyte sensorusage life expires, the predetermined monitoring time period has notended, and the expired analyte sensor is replaced with another analytesensor during the same predetermined monitoring time period. Thepredetermined monitoring time period in certain embodiments includes thereplacement of multiple analyte sensors for use.

Analyte level trend information in certain embodiments is generated orconstructed based on stored analyte level information spanning a timeperiod (e.g., corresponding to a temperature time period, or other) andcommunicated to the display device. The trend information in certainembodiments is output graphically and/or audibly and/or tactilely,and/or numerically and/or otherwise presented on a user interface of thedisplay device to provide indication of the analyte level variationduring this time period.

Embodiments include wirelessly communicating analyte level informationfrom an on body electronics device to a second device such as a displaydevice. Examples of communication protocols between on body electronicsand the display device may include radio frequency identification (RFID)protocols or RF communication protocols. Example RFID protocols includebut are not limited to Near Field Communication (NFC) protocols thatinclude short communication ranges (e.g., about 12 inches or less, orabout 6 inches or less, or about 3 inches or less, or about 2 inches orless), high frequency wireless communication protocols, far fieldcommunication protocols (e.g., using ultra high frequency (UHF)communication systems) for providing signals or data from on bodyelectronics to display devices.

Communication protocols in certain embodiments use 433 MHz frequency,13.56 MHz frequency, 2.45 GHz frequency, or other suitable frequenciesfor wireless communication between the on body electronics that includeselectronics coupled to an analyte sensor, and one or more displaydevices and/or other devices such as a personal computer. While certaindata transmission frequencies and/or data communication ranges aredescribed above, within the scope of the present disclosure, other datasuitable data transmission frequencies and/or data communication rangescan be used between the various devices in the analyte monitoringsystem.

Embodiments include data management systems including, for example, adata network and/or personal computer and/or a server terminal and/orone or more remote computers that are configured to receive collected orstored data from the display device for presenting analyte informationand/or further processing in conjunction with the physiologicalmonitoring for health management. For example, a display device mayinclude one or more communication ports (hard wired or wireless) forconnection to a data network or a computer terminal to transfercollected or stored analyte related data to another device and/orlocation. Analyte related data in certain embodiments are directlycommunicated from the electronics coupled to the analyte sensor to apersonal computer, server terminal, and/or remote computers over thedata network.

In certain embodiments, analyte information is only provided or evidentto a user (provided at a user interface device) when desired by the usereven though an in vivo analyte sensor automatically and/or continuouslymonitors the analyte level in vivo, e.g., the sensor automaticallymonitors analyte such as glucose on a pre-defined time interval over itsusage life. For example, an analyte sensor may be positioned in vivo andcoupled to on body electronics for a given sensing period, e.g., about14 days, about 21 days, or about 30 days or more. In certainembodiments, the sensor-derived analyte information is automaticallycommunicated from the sensor electronics assembly to a remote monitordevice or display device for output to a user throughout the 14 dayperiod according to a schedule programmed at the on body electronics(e.g., about every 1 minute or about every 5 minutes or about every 10minutes, or the like). In certain embodiments, sensor-derived analyteinformation is only communicated from the sensor electronics assembly toa remote monitor device or display device at user-determined times,e.g., whenever a user decides to check analyte information. At suchtimes, a communications system is activated and sensor-derivedinformation is then sent from the on body electronics to the remotedevice or display device. For example, using RFID communication, in oneembodiment, the user positions the display device in close proximity tothe on body electronics coupled to the analyte sensor and receives thereal time (and/or historical) analyte level information from the on bodyelectronics (herein after referred to as “on demand” reading).

In still other embodiments, the information may be communicated from afirst device to a second device automatically and/or continuously whenthe analyte information is available, and the second device stores orlogs the received information without presenting or outputting theinformation to the user. In such embodiments, the information isreceived by the second device from the first device when the informationbecomes available (e.g., when the sensor detects the analyte levelaccording to a time schedule). However, the received information isinitially stored in the second device and only output to a userinterface or an output component of the second device (e.g., display)upon detection of a request for the information on the second device.

Accordingly, in certain embodiments once a sensor electronics assemblyis placed on the body so that at least a portion of the in vivo sensoris in contact with bodily fluid and the sensor is electrically coupledto the electronics unit, sensor derived analyte information may becommunicated from the on body electronics to a display device on-demandby powering on the display device (or it may be continually powered),and executing a software algorithm stored in and accessed from a memoryof the display device, to generate one or more request commands, controlsignal or data packet to send to the on body electronics. The softwarealgorithm executed under, for example, the control of the microprocessoror application specific integrated circuit (ASIC) of the display devicemay include routines to detect the position of the on body electronicsrelative to the display device to initiate the transmission of thegenerated request command, control signal and/or data packet.

Display devices may also include programming stored in memory forexecution by one or more microprocessors and/or ASICs to generate andtransmit the one or more request command, control signal or data packetto send to the on body electronics in response to a user activation ofan input mechanism on the display device such as depressing a button onthe display device, triggering a soft button associated with the datacommunication function, and so on. The input mechanism may bealternatively or additionally provided on or in the on body electronicswhich may be configured for user activation. In certain embodiments,voice commands or audible signals may be used to prompt or instruct themicroprocessor or ASIC to execute the software routine(s) stored in thememory to generate and transmit the one or more request command, controlsignal or data packet to the on body device. In the embodiments that arevoice activated or responsive to voice commands or audible signals, onbody electronics and/or display device includes a microphone, a speaker,and processing routines stored in the respective memories of the on bodyelectronics and/or the display device to process the voice commandsand/or audible signals. In certain embodiments, positioning the on bodydevice and the display device within a predetermined distance (e.g.,close proximity) relative to each other initiates one or more softwareroutines stored in the memory of the display device to generate andtransmit a request command, control signal or data packet.

Different types and/or forms and/or amounts of information may be sentfor each on demand reading, including but not limited to one or more ofcurrent analyte level information (e.g., real time or the most recentlyobtained analyte level information temporally corresponding to the timethe reading is initiated), rate of change of an analyte over apredetermined time period, rate of the rate of change of an analyte(acceleration in the rate of change), historical analyte informationcorresponding to analyte information obtained prior to a given readingand stored in memory of the assembly. Some or all of real time,historical, rate of change, rate of rate of change (such as accelerationor deceleration) information may be sent to a display device for a givenreading. In certain embodiments, the type and/or form and/or amount ofinformation sent to a display device may be preprogrammed and/orunchangeable (e.g., preset at manufacturing), or may not bepreprogrammed and/or unchangeable so that it may be selectable and/orchangeable in the field one or more times (e.g., by activating a switchof the system, etc.).

Accordingly, in certain embodiments, for each on demand reading, adisplay device will output a current (real time) sensor-derived analytevalue (e.g., in numerical format), a current rate of analyte change(e.g., in the form of an analyte rate indicator such as an arrowpointing in a direction to indicate the current rate), and analyte trendhistory data based on sensor readings acquired by and stored in memoryof on body electronics (e.g., in the form of a graphical trace).Additionally, the on skin or sensor temperature reading or measurementassociated with each on demand reading may be communicated from the onbody electronics to the display device. The temperature reading ormeasurement, however, may not be output or displayed on the displaydevice, but rather, used in conjunction with a software routine executedby the display device to correct or compensate the analyte measurementoutput to the user on the display device.

As described, embodiments include in vivo analyte sensors and on bodyelectronics that together provide body wearable sensor electronicsassemblies. In certain embodiments, in vivo analyte sensors are fullyintegrated with on body electronics (fixedly connected duringmanufacture), while in other embodiments they are separate butconnectable post manufacture (e.g., before, during or after sensorinsertion into a body). On body electronics may include an in vivoglucose sensor, electronics, battery, and antenna encased (except forthe sensor portion that is for in vivo positioning) in a waterproofhousing that includes or is attachable to an adhesive pad. In certainembodiments, the housing withstands immersion in about one meter ofwater for up to at least 30 minutes. In certain embodiments, the housingwithstands continuous underwater contact, e.g., for longer than about 30minutes, and continues to function properly according to its intendeduse, e.g., without water damage to the housing electronics where thehousing is suitable for water submersion.

Embodiments include sensor insertion devices, which also may be referredto herein as sensor delivery units, or the like. Insertion devices mayretain on body electronics assemblies completely in an interiorcompartment, e.g., an insertion device may be “pre-loaded” with on bodyelectronics assemblies during the manufacturing process (e.g., on bodyelectronics may be packaged in a sterile interior compartment of aninsertion device). In such embodiments, insertion devices may formsensor assembly packages (including sterile packages) for pre-use or newon body electronics assemblies, and insertion devices configured toapply on body electronics assemblies to recipient bodies.

Embodiments include portable handheld display devices, as separatedevices and spaced apart from an on body electronics assembly, thatcollect information from the assemblies and provide sensor derivedanalyte readings to users. Such devices can be referred to in a numberof ways that have already been set forth. Certain embodiments mayinclude an integrated in vitro analyte meter. In certain embodiments,display devices include one or more wired or wireless communicationsports such as USB, serial, parallel, or the like, configured toestablish communication between a display device and another unit (e.g.,on body electronics, power unit to recharge a battery, a PC, etc.). Forexample, a display device communication port may enable charging adisplay device battery with a respective charging cable and/or dataexchange between a display device and its compatible informaticssoftware.

Compatible informatics software in certain embodiments include, forexample, but not limited to stand alone or network connection enableddata management software program, resident or running on a displaydevice, personal computer, a server terminal, for example, to performdata analysis, charting, data storage, data archiving and datacommunication as well as data synchronization. Informatics software incertain embodiments may also include software for executing fieldupgradable functions to upgrade firmware of a display device and/or onbody electronics unit to upgrade the resident software on the displaydevice and/or the on body electronics unit, e.g., with versions offirmware that include additional features and/or include software bugsor errors fixed, etc.

Embodiments include programming embedded on a computer readable medium,e.g., computer-based application software (may also be referred toherein as informatics software or programming or the like) thatprocesses analyte information obtained from the system and/or userself-reported data. Application software may be installed on a hostcomputer such as a mobile telephone, PC, an Internet-enabled humaninterface device such as an Internet-enabled phone, personal digitalassistant, or the like, by a display device or an on body electronicsunit. Informatics programming may transform data acquired and stored ona display device or on body unit for use by a user.

As described in detail below, embodiments include devices, systems, kitsand/or methods to monitor one or more physiological parameters such as,for example, but not limited to, analyte levels, temperature levels,heart rate, user activity level, over a predetermined monitoring timeperiod. Also provided are methods of manufacturing. Predeterminedmonitoring time periods may be less than about 1 hour, or may includeabout 1 hour or more, e.g., about a few hours or more, e.g., about a fewdays of more, e.g., about 3 or more days, e.g., about 5 days or more,e.g., about 7 days or more, e.g., about 10 days or more, e.g., about 14days or more, e.g., about several weeks, e.g., about 1 month or more. Incertain embodiments, after the expiration of the predeterminedmonitoring time period, one or more features of the system may beautomatically deactivated or disabled at the on body electronicsassembly and/or display device.

For example, a predetermined monitoring time period may begin withpositioning the sensor in vivo and in contact with a bodily fluid suchas interstitial fluid, and/or with the initiation (or powering on tofull operational mode) of the on body electronics. Initialization of onbody electronics may be implemented with a command generated andtransmitted by a display device in response to the activation of aswitch and/or by placing the display device within a predetermineddistance (e.g., close proximity) to the on body electronics, or by usermanual activation of a switch on the on body electronics unit, e.g.,depressing a button, or such activation may be caused by the insertiondevice, e.g., as described in U.S. Patent Publication No.2011/0213225A1, the disclosure of which is incorporated by reference inits entirety.

When initialized in response to a received command from a displaydevice, the on body electronics retrieves and executes from its memorysoftware routine to fully power on the components of the on bodyelectronics, effectively placing the on body electronics in fulloperational mode in response to receiving the activation command fromthe display device. For example, prior to the receipt of the commandfrom the display device, a portion of the components in the on bodyelectronics may be powered by its internal power supply such as abattery while another portion of the components in the on bodyelectronics may be in powered down or low power including no power,inactive mode, or all components may be in an inactive mode, powereddown mode. Upon receipt of the command, the remaining portion (or all)of the components of the on body electronics is switched to active,fully operational mode.

Embodiments of on body electronics may include one or more printedcircuit boards with electronics including control logic implemented inASIC, microprocessors, memory, and the like, and transcutaneouslypositionable analyte sensors forming a single assembly. On bodyelectronics may be configured to provide one or more signals or datapackets associated with a monitored analyte level upon detection of adisplay device of the analyte monitoring system within a predeterminedproximity for a period of time (for example, about 2 minutes, e.g., 1minute or less, e.g., about 30 seconds or less, e.g., about 10 secondsor less, e.g., about 5 seconds or less, e.g., about 2 seconds or less)and/or until a confirmation, such as an audible and/or visual and/ortactile (e.g., vibratory) notification, is output on the display deviceindicating successful acquisition of the analyte related signal from theon body electronics. A distinguishing notification may also be outputfor unsuccessful acquisition in certain embodiments.

In certain embodiments, the monitored analyte level may be correlatedand/or converted to glucose levels in blood or other bodily fluids. Suchconversion may be accomplished by the on body electronics, but in otherembodiments, will be accomplished with display device electronics.

Referring now to FIG. 1 , the analyte monitoring system 100 includes ananalyte sensor 101, a data processing unit 102 connectable to the sensor101, and a primary receiver unit or display device 104. In someinstances, the primary display device 104 is configured to communicatewith the data processing unit 102 via a communication link 103. Incertain embodiments, the primary display device 104 may be furtherconfigured to transmit data to a data processing terminal 105 toevaluate or otherwise process or format data received by the primarydisplay device 104. The data processing terminal 105 may be configuredto receive data directly from the data processing unit 102 via acommunication link 107, which may optionally be configured forbi-directional communication. Further, the data processing unit 102 mayinclude electronics and a transmitter or a transceiver to transmitand/or receive data to and/or from the primary display device 104 and/orthe data processing terminal 105 and/or optionally a secondary receiverunit or display device 106.

Also shown in FIG. 1 is an optional secondary display device 106 whichis operatively coupled to the communication link 103 and configured toreceive data transmitted from the data processing unit 102. Thesecondary display device 106 may be configured to communicate with theprimary display device 104, as well as the data processing terminal 105.In certain embodiments, the secondary display device 106 may beconfigured for bi-directional wireless communication with each of theprimary display device 104 and the data processing terminal 105. Asdiscussed in further detail below, in some instances, the secondarydisplay device 106 may be a de-featured receiver as compared to theprimary display device 104, for instance, the secondary display device106 may include a limited or minimal number of functions and features ascompared with the primary display device 104. As such, the secondarydisplay device 106 may include a smaller (in one or more, including all,dimensions), compact housing or embodied in a device including a wristwatch, arm band, PDA, mp3 player, cell phone, etc., for example.Alternatively, the secondary display device 106 may be configured withthe same or substantially similar functions and features as the primarydisplay device 104. The secondary display device 106 may include adocking portion configured to mate with a docking cradle unit forplacement by, e.g., the bedside for night time monitoring, and/or abi-directional communication device. A docking cradle may recharge apower supply.

Only one analyte sensor 101, data processing unit 102 and dataprocessing terminal 105 are shown in the embodiment of the analytemonitoring system 100 illustrated in FIG. 1 . However, it will beappreciated by one of ordinary skill in the art that the analytemonitoring system 100 may include more than one sensor 101 and/or morethan one data processing unit 102, and/or more than one data processingterminal 105. Multiple sensors may be positioned in a user for analytemonitoring at the same or different times. In certain embodiments,analyte information obtained by a first sensor positioned in a user maybe employed as a comparison to analyte information obtained by a secondsensor. This may be useful to confirm or validate analyte informationobtained from one or both of the sensors. Such redundancy may be usefulif analyte information is contemplated in critical therapy-relateddecisions. In certain embodiments, a first sensor may be used tocalibrate a second sensor.

In a multi-component environment, each component may be configured to beuniquely identified by one or more of the other components in the systemso that communication conflict may be readily resolved between thevarious components within the analyte monitoring system 100. Forexample, unique IDs, communication channels, and the like, may be used.

In certain embodiments, the sensor 101 is physically positioned in or onthe body of a user whose analyte level is being monitored. The sensor101 may be configured to at least periodically sample the analyte levelof the user and convert the sampled analyte level into a correspondingsignal for transmission by the data processing unit 102. The dataprocessing unit 102 is coupleable to the sensor 101 so that both devicesare positioned in or on the user's body, with at least a portion of theanalyte sensor 101 positioned transcutaneously. The data processing unit102 may include a fixation element, such as an adhesive or the like, tosecure it to the user's body. A mount (not shown) attachable to the userand mateable with the data processing unit 102 may be used. For example,a mount may include an adhesive surface. The data processing unit 102performs data processing functions, where such functions may include,but are not limited to, filtering and encoding of data signals, each ofwhich corresponds to a sampled analyte level of the user, fortransmission to the primary display device 104 via the communicationlink 103. In some embodiments, the sensor 101 or the data processingunit 102 or a combined sensor/data processing unit may be whollyimplantable under the skin surface of the user.

In certain embodiments, the primary display device 104 may include ananalog interface section including an RF receiver and an antenna that isconfigured to communicate with the data processing unit 102 via thecommunication link 103, and a data processing section for processing thereceived data from the data processing unit 102 including data decoding,error detection and correction, data clock generation, data bitrecovery, etc., or any combination thereof.

In operation, the primary display device 104 in certain embodiments isconfigured to synchronize with the data processing unit 102 to uniquelyidentify the data processing unit 102, based on, for example, anidentification information of the data processing unit 102, andthereafter, to periodically receive signals transmitted from the dataprocessing unit 102 associated with the monitored analyte levelsmonitored by the sensor 101.

Referring again to FIG. 1 , the data processing terminal 105 may includea personal computer, a portable computer including a laptop or ahandheld device (e.g., a personal digital assistant (PDA), a telephoneincluding a cellular phone (e.g., a multimedia and Internet-enabledmobile phone including an iPhone®, a Blackberry®, an Android phone, orsimilar phone), an mp3 player (e.g., an iPOD™, etc.), a pager, and thelike), and/or a drug delivery device (e.g., an infusion device), each ofwhich may be configured for data communication with the display devicesvia a wired or a wireless connection. Additionally, the data processingterminal 105 may further be connected to a data network (not shown) forstoring, retrieving, updating, and/or analyzing data corresponding tothe detected analyte level of the user.

The data processing terminal 105 may include a drug delivery device(e.g., an infusion device) such as an insulin infusion pump or the like,which may be configured to administer a drug (e.g., insulin) to theuser, and which may be configured to communicate with the primarydisplay device 104 for receiving, among others, the measured analytelevel. Alternatively, the primary display device 104 may be configuredto integrate an infusion device therein so that the primary displaydevice 104 is configured to administer an appropriate drug (e.g.,insulin) to users, for example, for administering and modifying basalprofiles, as well as for determining appropriate boluses foradministration based on, among others, the detected analyte levelsreceived from the data processing unit 102. An infusion device may be anexternal device or an internal device, such as a device whollyimplantable in a user.

In certain embodiments, the data processing terminal 105, which mayinclude an infusion device, e.g., an insulin pump, may be configured toreceive the analyte signals from the data processing unit 102, and thus,incorporate the functions of the primary display device 104 includingdata processing for managing the user's insulin therapy and analytemonitoring. In certain embodiments, the communication link 103, as wellas one or more of the other communication interfaces shown in FIG. 1 ,may use one or more wireless communication protocols, such as, but notlimited to: an RF communication protocol, an infrared communicationprotocol, a Bluetooth enabled communication protocol, an 802.11xwireless communication protocol, or an equivalent wireless communicationprotocol which would allow secure, wireless communication of severalunits (for example, per Health Insurance Portability and AccountabilityAct (HIPPA) requirements), while avoiding potential data collision andinterference.

FIG. 2 is a block diagram depicting an embodiment of a data processingunit 102 of the analyte monitoring system shown in FIG. 1 . User inputand/or interface components may be included or a data processing unitmay be free of user input and/or interface components. In certainembodiments, one or more application-specific integrated circuits (ASIC)(e.g., having processing circuitry and non-transitory memory for storingsoftware instructions for execution by the processing circuitry) may beused to implement one or more functions or routines associated with theoperations of the data processing unit (and/or display device) using forexample one or more state machines and buffers.

As can be seen in the embodiment of FIG. 2 , the analyte sensor 101(FIG. 1 ) includes four contacts, three of which are electrodes: aworking electrode (W) 210, a reference electrode (R) 212, and a counterelectrode (C) 213, each operatively coupled to the analog interface 201of the data processing unit 102. This embodiment also shows an optionalguard contact (G) 211. Fewer or greater electrodes may be employed. Forexample, the counter and reference electrode functions may be served bya single counter/reference electrode. In some cases, there may be morethan one working electrode and/or reference electrode and/or counterelectrode, etc.

FIG. 3 is a block diagram of an embodiment of a receiver/monitor unitsuch as the primary display device 104 of the analyte monitoring systemshown in FIG. 1 . The primary display device 104 includes one or moreof: a test strip interface 301, an RF receiver 302, a user input 303, anoptional temperature detection section 304, and a clock 305, each ofwhich is operatively coupled to a processing and storage section 307(that can include processing circuitry and non-transitory memory storingsoftware instructions for execution by the processing circuitry). Theprimary display device 104 also includes a power supply 306 operativelycoupled to a power conversion and monitoring section 308. Further, thepower conversion and monitoring section 308 is also coupled to theprocessing and storage section 307. Moreover, also shown are a receiverserial communication section 309, and an output 310, each operativelycoupled to the processing and storage section 307. The primary displaydevice 104 may include user input and/or interface components or may befree of user input and/or interface components.

In certain embodiments, the test strip interface 301 includes an analytetesting portion (e.g., a glucose level testing portion) to receive ablood (or other body fluid sample) analyte test or information relatedthereto. For example, the test strip interface 301 may include a teststrip port to receive a test strip (e.g., a glucose test strip). Thedevice may determine the analyte level of the test strip, and optionallydisplay (or otherwise notice) the analyte level on the output 310 of theprimary display device 104. Any suitable test strip may be employed,e.g., test strips that only require a very small amount (e.g., 3microliters or less, e.g., 1 microliter or less, e.g., 0.5 microlitersor less, e.g., 0.1 microliters or less), of applied sample to the stripin order to obtain accurate glucose information. Glucose informationobtained by an in vitro glucose testing device may be used for a varietyof purposes, computations, etc. For example, the information may be usedto calibrate sensor 101 (FIG. 1 ), confirm results of sensor 101 toincrease the confidence thereof (e.g., in instances in which informationobtained by sensor 101 is employed in therapy related decisions), etc.

In further embodiments, the data processing unit 102 and/or the primarydisplay device 104 and/or the secondary display device 106, and/or thedata processing terminal/infusion device 105 may be configured toreceive the analyte value wirelessly over a communication link from, forexample, a blood glucose meter. In further embodiments, a usermanipulating or using the analyte monitoring system 100 may manuallyinput the analyte value using, for example, a user interface (forexample, a keyboard, keypad, voice commands, and the like) incorporatedin one or more of the data processing unit 102, the primary displaydevice 104, secondary display device 106, or the data processingterminal/infusion device 105.

FIG. 4 schematically shows an embodiment of an analyte sensor 400 inaccordance with the embodiments of the present disclosure. This sensorembodiment includes electrodes 401, 402 and 403 on a base 404.Electrodes (and/or other features) may be applied or otherwise processedusing any suitable technology, e.g., chemical vapor deposition (CVD),physical vapor deposition, sputtering, reactive sputtering, printing,coating, ablating (e.g., laser ablation), painting, dip coating,etching, and the like. Materials include, but are not limited to, anyone or more of aluminum, carbon (including graphite), cobalt, copper,gallium, gold, indium, iridium, iron, lead, magnesium, mercury (as anamalgam), nickel, niobium, osmium, palladium, platinum, rhenium,rhodium, selenium, silicon (e.g., doped polycrystalline silicon),silver, tantalum, tin, titanium, tungsten, uranium, vanadium, zinc,zirconium, mixtures thereof, and alloys, oxides, or metallic compoundsof these elements.

The analyte sensor 400 may be wholly implantable in a user or may beconfigured so that only a portion is positioned within (internal) a userand another portion outside (external) a user. For example, the sensor400 may include a first portion positionable above a surface of the skin410, and a second portion positioned below the surface of the skin. Insuch embodiments, the external portion may include contacts (connectedto respective electrodes of the second portion by traces) to connect toanother device also external to the user such as a sensor controldevice. While the embodiment of FIG. 4 shows three electrodesside-by-side on the same surface of base 404, other configurations arecontemplated, e.g., fewer or greater electrodes, some or all electrodeson different surfaces of the base or present on another base, some orall electrodes stacked together, electrodes of differing materials anddimensions, etc.

FIG. 5A shows a perspective view of an embodiment of an analyte sensor500 having a first portion (which in this embodiment may becharacterized as a major portion) positionable above a surface of theskin 510, and a second portion (which in this embodiment may becharacterized as a minor portion) that includes an insertion tip 530positionable below the surface of the skin, e.g., penetrating throughthe skin and into, e.g., the subcutaneous space 520, in contact with theuser's biofluid, such as interstitial fluid. Contact portions of aworking electrode 511, a reference electrode 512, and a counterelectrode 513 are positioned on the first portion of the sensor 500situated above the skin surface 510. A working electrode 501, areference electrode 502, and a counter electrode 503 are shown at thesecond portion of the sensor 500 and particularly at the insertion tip530. Traces may be provided from the electrodes at the tip 530 to thecontacts, as shown in FIG. 5A. It is to be understood that greater orfewer electrodes may be provided on a sensor. For example, a sensor mayinclude more than one working electrode and/or the counter and referenceelectrodes may be a single counter/reference electrode, etc.

FIG. 5B shows a cross sectional view of a portion of the sensor 500 ofFIG. 5A. The electrodes 501, 509/502 and 503, of the sensor 500 as wellas the substrate and the dielectric layers are provided in a layeredconfiguration or construction. For example, as shown in FIG. in oneembodiment, the sensor 500 (such as the analyte sensor 101 of FIG. 1 ),includes a substrate layer 504, and a first conducting layer 501 such ascarbon, gold, etc., disposed on at least a portion of the substratelayer 504, and which may provide the working electrode. Also showndisposed on at least a portion of the first conducting layer 501 is asensing region 508.

A first insulation layer 505, such as a first dielectric layer incertain embodiments, is disposed or layered on at least a portion of thefirst conducting layer 501, and further, a second conducting layer 509may be disposed or stacked on top of at least a portion of the firstinsulation layer (or dielectric layer) 505. As shown in FIG. 5B, thesecond conducting layer 509 in conjunction with a second conductingmaterial 502, such as a layer of silver/silver chloride (Ag/AgCl), mayprovide the reference electrode.

A second insulation layer 506, such as a second dielectric layer incertain embodiments, may be disposed or layered on at least a portion ofthe second conducting layer 509. Further, a third conducting layer 503may be disposed on at least a portion of the second insulation layer 506and may provide the counter electrode 503. Finally, a third insulationlayer 507 may be disposed or layered on at least a portion of the thirdconducting layer 503. In this manner, the sensor 500 may be layered suchthat at least a portion of each of the conducting layers is separated bya respective insulation layer (for example, a dielectric layer). Theembodiments of FIGS. 5A and 5B show the layers having different lengths.In certain instances, some or all of the layers may have the same ordifferent lengths and/or widths.

In certain embodiments, some or all of the electrodes 501, 502, 503 maybe provided on the same side of the substrate 504 in the layeredconstruction as described above, or alternatively, may be provided in aco-planar manner such that two or more electrodes may be positioned onthe same plane (e.g., side-by side (e.g., parallel) or angled relativeto each other) on the substrate 504. For example, co-planar electrodesmay include a suitable spacing therebetween and/or include a dielectricmaterial or insulation material disposed between the conductinglayers/electrodes.

Furthermore, in certain embodiments, one or more of the electrodes 501,502, 503 may be disposed on opposing sides of the substrate 504. In suchembodiments, contact pads may be on the same or different sides of thesubstrate. For example, an electrode may be on a first side and itsrespective contact may be on a second side, e.g., a trace connecting theelectrode and the contact may traverse through the substrate.

Embodiments of a double-sided, stacked sensor configuration which may beutilized in connection with the present disclosure are described belowwith reference to FIGS. 6-8 . FIG. 6 shows a cross-sectional view of adistal portion of a double-sided analyte sensor 600. Analyte sensor 600includes an at least generally planar insulative base substrate 601,e.g., an at least generally planar dielectric base substrate, having afirst conductive layer 602 which substantially covers the entirety of afirst surface area, e.g., the top surface area, of insulative substrate601, e.g., the conductive layer substantially extends the entire lengthof the substrate to the distal edge and across the entire width of thesubstrate from side edge to side edge. A second conductive layer 603substantially covers the entirety of a second surface, e.g., the bottomside, of insulative base substrate 601. However, one or both of theconductive layers may terminate proximally of the distal edge and/or mayhave a width which is less than that of insulative substrate 601 wherethe width ends a selected distance from the side edges of the substrate,which distance may be equidistant or vary from each of the side edges.

One of the first or second conductive layers, e.g., first conductivelayer 602, may be configured to include the sensor's working electrode.The opposing conductive layer, here, second conductive layer 603, may beconfigured to include a reference and/or counter electrode. Whereconductive layer 603 serves as either a reference or counter electrode,but not both, a third electrode may optionally be provided either on asurface area of the proximal portion of the sensor (not shown), on aseparate substrate, or as an additional conductive layer positionedeither above or below conductive layer 602 or 603 and separated fromthose layers by an insulative layer or layers. For example, in someembodiments, where analyte sensor 600 is configured to be partiallyimplanted, conductive layer 603 may be configured to include a referenceelectrode, and a third electrode (not shown) and present only on anon-implanted proximal portion of the sensor may be configured toinclude the sensor's counter electrode.

A first insulative layer 604 covers at least a portion of conductivelayer 602 and a second insulative layer 605 covers at least a portion ofconductive layer 603. In one embodiment, at least one of firstinsulative layer 604 and second insulative layer 605 does not extend tothe distal end of analyte sensor 600 leaving an exposed region of theconductive layer or layers.

FIG. 7 shows a cross-sectional view of a distal portion of adouble-sided analyte sensor 700 including an at least generally planarinsulative base substrate 701, e.g., an at least generally planardielectric base substrate, having a first conductive layer 702 whichsubstantially covers the entirety of a first surface area, e.g., the topsurface area, of insulative substrate 701, e.g., the conductive layersubstantially extends the entire length of the substrate to the distaledge and across the entire width of the substrate from side edge to sideedge. A second conductive layer 703 substantially covers the entirety ofa second surface, e.g., the bottom side, of insulative base substrate701. However, one or both of the conductive layers may terminateproximally of the distal edge and/or may have a width which is less thanthat of insulative substrate 701 where the width ends a selecteddistance from the side edges of the substrate, which distance may beequidistant or vary from each of the side edges.

In the embodiment of FIG. 7 , conductive layer 702 is configured toinclude a working electrode which includes a sensing region 702Adisposed on at least a portion of the first conductive layer 702 asshown and as discussed in greater detail below. While a single sensingregion 702A is shown, it should be noted that in other embodiments aplurality of spatially separated sensing elements may be utilized.

In the embodiment of FIG. 7 , conductive layer 703 is configured toinclude a reference electrode which includes a secondary layer ofconductive material 703A, e.g., Ag/AgCl, disposed over a distal portionof conductive layer 703.

A first insulative layer 704 covers a portion of conductive layer 702and a second insulative layer 705 covers a portion of conductive layer703. First insulative layer 704 does not extend to the distal end ofanalyte sensor 700 leaving an exposed region of the conductive layerwhere the sensing region 702A is positioned. The insulative layer 705 onthe bottom/reference electrode side of the sensor, may extend anysuitable length of the sensor's distal section, e.g., it may extend theentire length of both of the primary and secondary conductive layers orportions thereof. For example, as illustrated in FIG. 7 , bottominsulative layer 705 extends over the entire bottom surface area ofsecondary conductive material 703A but terminates proximally of thedistal end of the length of the conductive layer 703. It is noted thatat least the ends of the secondary conductive material 703A which extendalong the side edges of the substrate 701 are not covered by insulativelayer 705 and, as such, are exposed to the environment when in operativeuse.

In an alternative embodiment, as shown in FIG. 8 , analyte sensor 800has an insulative layer 804 on the working electrode side of aninsulative base substrate 801, which may be provided prior to sensingregion 802A whereby the insulative layer 804 has at least two portionsspaced apart from each other on conductive layer 802. The sensing region802A is then provided in the spacing between the two portions. More thantwo spaced apart portions may be provided, e.g., where a plurality ofsensing components or layers is desired. Bottom insulative layer 805 hasa length which terminates proximally of secondary conductive layer 803Aon bottom primary conductive layer 803. Additional conducting anddielectric layers may be provided on either or both sides of thesensors, as described above.

While FIGS. 6-8 depict or are discussed herein as capable of providingthe working and reference electrodes in a particular layeredconfiguration, it should be noted that the relative positioning of theselayers may be modified. For example, a counter electrode layer may beprovided on one side of an insulative base substrate while working andreference electrode layers are provided in a stacked configuration onthe opposite side of the insulative base substrate. In addition, adifferent number of electrodes may be provided than depicted in FIGS.6-8 by adjusting the number of conductive and insulative layers. Forexample, a 3 or four electrode sensor may be provided.

One or more membranes, which may function as one or more of an analyteflux modulating layer and/or an interferent-eliminating layer and/orbiocompatible layer, discussed in greater detail below, may be includedwith, on or about the sensor, e.g., as one or more of the outermostlayer(s). Those of ordinary skill in the art will readily recognize thatthe membrane can take many forms. The membrane can include just onecomponent, or multiple components. The membrane can have a globularshape, such as if encompassing a terminal region of the sensor (e.g.,the lateral sides and terminal tip). The membrane can have a generallyplanar structure, and can be characterized as a layer. Planar membranescan be smooth or can have minor surface (topological) variations. Themembrane can also be configured as other non-planar structures. Forexample, the membrane can have a cylindrical shape or a partiallycylindrical shape, a hemispherical shape or other partially sphericalshape, an irregular shape, or other rounded or curved shape.

In certain embodiments, as illustrated in FIG. 7 , a first membranelayer 706 may be provided solely over the sensing region 702A on theworking electrode 702 to modulate the rate of diffusion or flux of theanalyte to the sensing region. For embodiments in which a membrane layeris provided over a single component/material, it may be suitable to doso with the same striping configuration and method as used for the othermaterials/components. Here, the membrane material 706 preferably has awidth greater than that of sensing component 702A. As it acts to limitthe flux of the analyte to the sensor's active area, and thuscontributes to the sensitivity of the sensor, controlling the thicknessof membrane 706 is important. Providing membrane 706 in the form of astripe/band facilitates control of its thickness. A second membranelayer 707, which coats the remaining surface area of the sensor tail,may also be provided to serve as a biocompatible conformal coating andprovide smooth edges over the entirety of the sensor. In other sensorembodiments, as illustrated in FIG. 8 , a single, homogenous membrane806 may be coated over the entire sensor surface area, or at least overboth sides of the distal tail portion. It is noted that to coat thedistal and side edges of the sensor, the membrane material may have tobe applied subsequent to singulation of the sensor precursors. In someembodiments, the analyte sensor is dip-coated following singulation toapply one or more membranes. Alternatively, the analyte sensor could beslot-die coated wherein each side of the analyte sensor is coatedseparately.

FIG. 9 shows a cross-sectional view of a distal portion of an exampledouble-sided analyte sensor 900 according to one embodiment of thepresent disclosure, wherein the double-sided analyte sensor includes anat least generally planar insulative base substrate 901, e.g., an atleast generally planar dielectric base substrate, having a firstconductive layer 902. A second conductive layer 903 is positioned on afirst side, e.g., the bottom side, of insulative base substrate 901.While depicted as extending to the distal edge of the sensor, one orboth of the conductive layers may terminate proximally of the distaledge and/or may have a width which is less than that of insulativesubstrate 901 where the width ends a selected distance from the sideedges of the substrate, which distance may be equidistant or vary fromeach of the side edges. See, for example, the analyte sensor assembly900, discussed in more detail below, wherein first and second conductivelayers are provided which define electrodes, including, e.g., electrodetraces, which have widths which are less than that of the insulativebase substrate.

In the embodiment of FIG. 9 , conductive layer 903 is configured toinclude a working electrode which includes a sensing region 908 disposedon at least a portion of the conductive layer 903, which sensing regionis discussed in greater detail below. It should be noted that aplurality of spatially separated sensing components or layers may beutilized in forming the working electrode, e.g., one or more sensing“dots” or areas may be provided on the conductive layer 903, as shownherein, or a single sensing component may be used (not shown).

In the embodiment of FIG. 9 , conductive layer 906 is configured toinclude a reference electrode which includes a secondary layer ofconductive material 906A, e.g., Ag/AgCl, disposed on a distal portion ofconductive layer 906. Like conductive layers 902 and 903, conductivelayer 906 may terminate proximally of the distal edge and/or may have awidth which is less than that of insulative substrate 901 where thewidth ends a selected distance from the side edges of the substrate,which distance may be equidistant or vary from each of the side edges,as discussed in greater detail below in reference to FIGS. 10A-10C.

In the embodiment shown in FIG. 9 , conductive layer 902 is configuredto include a counter electrode. A first insulative layer 904 covers aportion of conductive layer 902 and a second insulative layer 905 coversa portion of conductive layer 903. First insulative layer 904 does notextend to the distal end of analyte sensor 900 leaving an exposed regionof the conductive layer 902 which acts as the counter electrode. Aninsulative layer 905 covers a portion of conductive layer 903 leaving anexposed region of the conductive layer 903 where the sensing region 908is positioned. As discussed above, multiple spatially separated sensingcomponents or layers may be provided (as shown) in some embodiments,while in other embodiments a single sensing region may be provided. Theinsulative layer 907 on a first side, e.g., the bottom side of thesensor (in the view provided by FIG. 9 ), may extend any suitable lengthof the sensor's distal section, e.g., it may extend the entire length ofboth of conductive layers 906 and 906A or portions thereof. For example,as illustrated in FIG. 9 , bottom insulative layer 907 extends over theentire bottom surface area of secondary conductive material 906A andterminates distally of the distal end of the length of the conductivelayer 906. It is noted that at least the ends of the secondaryconductive material 906A which extend along the side edges of thesubstrate 901 are not covered by insulative layer 907 and, as such, areexposed to the environment when in operative use.

As illustrated in FIG. 9 , a homogenous membrane 909 may be coated overthe entire sensor surface area, or at least over both sides of thedistal tail portion. It is noted that to coat the distal and side edgesof the sensor, the membrane material may have to be applied subsequentto singulation of the sensor precursors. In some embodiments, theanalyte sensor is dip-coated following singulation to apply one or moremembranes (or to apply one membrane in various stages). Alternatively,the analyte sensor could be slot-die coated wherein each side of theanalyte sensor is coated separately. Membrane 909 is shown in FIG. 9 ashaving a squared shape matching the underlying surface variations, butcan have a more globular or amorphous shape as well.

When manufacturing layered sensors, it may be desirable to utilizerelatively thin insulative layers to reduce total sensor width. Forexample, with reference to FIG. 9 , insulative layers 904, 905 and 907may be relatively thin relative to insulative substrate layer 901. Forexample, insulative layers 904, 905 and 907 may have a thickness in therange of 20-25 μm while substrate layer 901 has a thickness in the rangeof 0.1 to 0.15 mm. However, during singulation of the sensors where suchsingulation is accomplished by cutting through two or more conductivelayers which are separated by such thin insulative layers, shortingbetween the two conductive layers may occur.

One method of addressing this potential issue is to provide one of theconductive layers, e.g., electrodes layers, at least in part as arelatively narrow electrode, including, e.g., a relatively narrowconductive trace, such that during the singulation process the sensor iscut on either side of the narrow electrode such that one electrode iscut without cutting through the narrow electrode.

For example, with reference to FIGS. 10A-10C, a sensor 1000 is depictedwhich includes insulative layers 1003 and 1005. Insulative layers 1003and 1005 may be thin relative to generally planar insulative basesubstrate layer 1001, or vice versa. For example, insulative layers 1003and 1005 may have a thickness in the range of 15-30 μm while substratelayer 1001 has a thickness in the range of 0.1 to 0.15 mm. Such sensorsmay be manufactured in sheets wherein a single sheet includes aplurality of sensors. However, such a process generally requiressingulation of the sensors prior to use. Where such singulation requirescutting through two or more conductive layers which are separated byinsulative layers, shorting between the two conductive layers may occur,particularly if the insulative layers are thin. In order to avoid suchshorting, fewer than all of the conductive layers may be cut throughduring the singulation process. For example, at least one of theconductive layers may be provided at least in part as an electrode,e.g., including a conductive trace, having a narrow width relative toone or more other conductive layers such that during the singulationprocess a first conductive layer separated from a second conductivelayer only by a thin insulative layer, e.g., an insulative layer havinga thickness in the range of 15-30 μm, is cut while a second conductivelayer is not.

For example, with reference to FIGS. 10A and 10C, a sensor 1000 includesan at least generally planar insulative base substrate 1001. Positionedon the at least generally planar insulative base substrate 1001 is afirst conductive layer 1002. A first relatively thin insulative layer1003, e.g., an insulative layer having a thickness in the range of 15-30μm, is positioned on the first conductive layer 1002 and secondconductive layer 1004 is positioned on the relatively thin insulativelayer 1003. Finally, a second relatively thin insulative layer 1005,e.g., an insulative layer having a thickness in the range of 15-30 μm,is positioned on the second conductive layer 1004.

As shown in FIG. 10B, first conductive layer 1002 may be an electrodehaving a narrow width relative to conductive layer 1004 as shown in theFIG. 10B cross-section taken at lines A-A. Alternatively, secondconductive layer 1004 may be a conductive electrode having a narrowwidth relative to conductive layer 1002 as shown in the FIG. 1Ccross-section taken at lines A-A. Singulation cut lines 1006 are shownin FIGS. 10B and 10C. The sensor may be singulated, for example, bycutting to either side of the relatively narrow conductive electrode,e.g., in regions 1007, as shown in FIGS. 10B and 10C. With reference toFIG. 10B, singulation by cutting along singulation cut lines 1006results in cutting through conductive layer 1004 but not conductivelayer 1002. With reference to FIG. 10C, singulation by cutting alongsingulation cut lines 1006 results in cutting through conductive layer1002 but not conductive layer 1004.

An embodiment of a sensing region may be described as the area shownschematically in FIG. 5B as 508 and FIG. 9 as 908. As noted above thesensing region may be provided as a single sensing component as shown inFIG. 5B as 508, FIG. 7 as 702A and FIG. 8 as 802A, or provided as aplurality of sensing components as shown in FIG. 9 as 908. A pluralityof sensing components or sensing “spots” is described in US PatentApplication Publication No. 2012/0150005, incorporated by referenceherein in its entirety.

The term “sensing region” is a broad term and may be described as theactive chemical area of the biosensor. Those of ordinary skill in theart will readily recognize that the sensing region can take many forms.The sensing region can include just one component, or multiplecomponents (e.g., such as sensing region 908 of FIG. 9 ). In theembodiment of FIG. 5B, for example, the sensing region is a generallyplanar structure, and can be characterized as a layer. Planar sensingregions can be smooth or can have minor surface (topological)variations. The sensing region can also be a non-planar structure. Forexample, the sensing region can have a cylindrical shape or a partiallycylindrical shape, a hemispherical shape or other partially sphericalshape, an irregular shape, or other rounded or curved shape.

The sensing region formulation, which can include a glucose-transducingagent, may include, for example, among other constituents, a redoxmediator, such as, for example, a hydrogen peroxide or a transitionmetal complex, such as a ruthenium-containing complex or anosmium-containing complex, and an analyte-responsive enzyme, such as,for example, a glucose-responsive enzyme (e.g., glucose oxidase, glucosedehydrogenase, etc.) or lactate-responsive enzyme (e.g., lactateoxidase). In certain embodiments, the sensing region includes glucoseoxidase. The sensing region may also include other optional components,such as, for example, a polymer and a bi-functional, short-chain,epoxide cross-linker, such as polyethylene glycol (PEG).

In certain instances, the analyte-responsive enzyme is distributedthroughout the sensing region. For example, the analyte-responsiveenzyme may be distributed uniformly throughout the sensing region, suchthat the concentration of the analyte-responsive enzyme is substantiallythe same throughout the sensing region. In some cases, the sensingregion may have a homogeneous distribution of the analyte-responsiveenzyme. In certain embodiments, the redox mediator is distributedthroughout the sensing region. For example, the redox mediator may bedistributed uniformly throughout the sensing region, such that theconcentration of the redox mediator is substantially the same throughoutthe sensing region. In some cases, the sensing region may have ahomogeneous distribution of the redox mediator. In certain embodiments,both the analyte-responsive enzyme and the redox mediator aredistributed uniformly throughout the sensing region, as described above.

As noted above, analyte sensors may include an analyte-responsive enzymeto provide a sensing component or sensing region. Some analytes, such asoxygen, can be directly electrooxidized or electroreduced on a sensor,and more specifically at least on a working electrode of a sensor. Otheranalytes, such as glucose and lactate, require the presence of at leastone electron transfer agent and/or at least one catalyst to facilitatethe electrooxidation or electroreduction of the analyte. Catalysts mayalso be used for those analytes, such as oxygen, that can be directlyelectrooxidized or electroreduced on the working electrode. For theseanalytes, each working electrode includes a sensing region (see forexample sensing region 508 of FIG. 5B) proximate to or on a surface of aworking electrode. In many embodiments, a sensing region is formed nearor on only a small portion of at least a working electrode.

The sensing region can include one or more components constructed tofacilitate the electrochemical oxidation or reduction of the analyte.The sensing region may include, for example, a catalyst to catalyze areaction of the analyte and produce a response at the working electrode,an electron transfer agent to transfer electrons between the analyte andthe working electrode (or other component), or both.

A variety of different sensing region configurations may be used. Thesensing region is often located in contact with or in proximity to anelectrode, such as the working electrode. In certain embodiments, thesensing region is deposited on the conductive material of the workingelectrode. The sensing region may extend beyond the conductive materialof the working electrode. In some cases, the sensing region may alsoextend over other electrodes, e.g., over the counter electrode and/orreference electrode (or if a counter/reference is provided).

A sensing region that is in direct contact with the working electrodemay contain an electron transfer agent to transfer electrons directly orindirectly between the analyte and the working electrode, and/or acatalyst to facilitate a reaction of the analyte. For example, aglucose, lactate, or oxygen electrode may be formed having a sensingregion which contains a catalyst, including glucose oxidase, glucosedehydrogenase, lactate oxidase, or laccase, respectively, and anelectron transfer agent that facilitates the electrooxidation of theglucose, lactate, or oxygen, respectively.

In other embodiments, the sensing region is not deposited directly onthe working electrode. Instead, the sensing region 508 (FIG. 5 ), forexample, may be spaced apart from the working electrode, and separatedfrom the working electrode, e.g., by a separation layer. A separationlayer may include one or more membranes or films or a physical distance.In addition to separating the working electrode from the sensing region,the separation layer may also act as a mass transport limiting layerand/or an interferent eliminating layer and/or a biocompatible layer.

In certain embodiments which include more than one working electrode,one or more of the working electrodes may not have a correspondingsensing region, or may have a sensing region which does not contain oneor more components (e.g., an electron transfer agent and/or catalyst)needed to electrolyze the analyte. Thus, the signal at this workingelectrode may correspond to background signal which may be removed fromthe analyte signal obtained from one or more other working electrodesthat are associated with fully-functional sensing regions by, forexample, subtracting the signal.

In certain embodiments, the sensing region includes one or more electrontransfer agents. Electron transfer agents that may be employed areelectroreducible and electrooxidizable ions or molecules having redoxpotentials that are a few hundred millivolts above or below the redoxpotential of the standard calomel electrode (SCE). The electron transferagent may be organic, organometallic, or inorganic. Examples of organicredox species are quinones and species that in their oxidized state havequinoid structures, such as Nile blue and indophenol. Examples oforganometallic redox species are metallocenes including ferrocene.Examples of inorganic redox species are hexacyanoferrate (III),ruthenium hexamine, etc. Additional examples include those described inU.S. Pat. Nos. 6,736,957, 7,501,053 and 7,754,093, the disclosures ofeach of which are incorporated herein by reference in their entirety.

In certain embodiments, electron transfer agents have structures orcharges which prevent or substantially reduce the diffusional loss ofthe electron transfer agent during the period of time that the sample isbeing analyzed. For example, electron transfer agents include but arenot limited to a redox species, e.g., bound to a polymer which can inturn be disposed on or near the working electrode. The bond between theredox species and the polymer may be covalent, coordinative, or ionic.Although any organic, organometallic or inorganic redox species may bebound to a polymer and used as an electron transfer agent, in certainembodiments the redox species is a transition metal compound or complex,e.g., osmium, ruthenium, iron, and cobalt compounds or complexes. Itwill be recognized that many redox species described for use with apolymeric component may also be used, without a polymeric component.

Embodiments of polymeric electron transfer agents may contain a redoxspecies covalently bound in a polymeric composition. An example of thistype of mediator is poly(vinylferrocene). Another type of electrontransfer agent contains an ionically-bound redox species. This type ofmediator may include a charged polymer coupled to an oppositely chargedredox species. Examples of this type of mediator include a negativelycharged polymer coupled to a positively charged redox species such as anosmium or ruthenium polypyridyl cation. Another example of anionically-bound mediator is a positively charged polymer includingquaternized poly(4-vinyl pyridine) or poly(l-vinyl imidazole) coupled toa negatively charged redox species such as ferricyanide or ferrocyanide.In other embodiments, electron transfer agents include a redox speciescoordinatively bound to a polymer. For example, the mediator may beformed by coordination of an osmium or cobalt 2,2′-bipyridyl complex topoly(l-vinyl imidazole) or poly(4-vinyl pyridine).

Suitable electron transfer agents are osmium transition metal complexeswith one or more ligands, each ligand having a nitrogen-containingheterocycle such as 2,2′-bipyridine, 1,10-phenanthroline, 1-methyl,2-pyridyl biimidazole, or derivatives thereof. The electron transferagents may also have one or more ligands covalently bound in a polymer,each ligand having at least one nitrogen-containing heterocycle, such aspyridine, imidazole, or derivatives thereof. One example of an electrontransfer agent includes (a) a polymer or copolymer having pyridine orimidazole functional groups and (b) osmium cations complexed with twoligands, each ligand containing 2,2′-bipyridine, 1,10-phenanthroline, orderivatives thereof, the two ligands not necessarily being the same.Some derivatives of 2,2′-bipyridine for complexation with the osmiumcation include but are not limited to 4,4′-dimethyl-2,2′-bipyridine andmono-, di-, and polyalkoxy-2,2′-bipyridines, including4,4′-dimethoxy-2,2′-bipyridine. Derivatives of 1,10-phenanthroline forcomplexation with the osmium cation include but are not limited to4,7-dimethyl-1,10-phenanthroline and mono, di-, andpolyalkoxy-1,10-phenanthrolines, such as4,7-dimethoxy-1,10-phenanthroline. Polymers for complexation with theosmium cation include but are not limited to polymers and copolymers ofpoly(1-vinyl imidazole) (referred to as “PVI”) and poly(4-vinylpyridine) (referred to as “PVP”). Suitable copolymer substituents ofpoly(1-vinyl imidazole) include acrylonitrile, acrylamide, andsubstituted or quaternized N-vinyl imidazole, e.g., electron transferagents with osmium complexed to a polymer or copolymer of poly(1-vinylimidazole).

Embodiments may employ electron transfer agents having a redox potentialranging from about −200 mV to about +200 mV versus the standard calomelelectrode (SCE). The sensing region may also include a catalyst which iscapable of catalyzing a reaction of the analyte. The catalyst may also,in some embodiments, act as an electron transfer agent. One example of asuitable catalyst is an enzyme which catalyzes a reaction of theanalyte. For example, a catalyst, including a glucose oxidase, glucosedehydrogenase (e.g., pyrroloquinoline quinone (PQQ), dependent glucosedehydrogenase, flavine adenine dinucleotide (FAD) dependent glucosedehydrogenase, or nicotinamide adenine dinucleotide (NAD) dependentglucose dehydrogenase), may be used when the analyte of interest isglucose. A lactate oxidase or lactate dehydrogenase may be used when theanalyte of interest is lactate. Laccase may be used when the analyte ofinterest is oxygen or when oxygen is generated or consumed in responseto a reaction of the analyte.

In certain embodiments, a catalyst may be attached to a polymer, crosslinking the catalyst with another electron transfer agent, which, asdescribed above, may be polymeric. A second catalyst may also be used incertain embodiments. This second catalyst may be used to catalyze areaction of a product compound resulting from the catalyzed reaction ofthe analyte. The second catalyst may operate with an electron transferagent to electrolyze the product compound to generate a signal at theworking electrode. Alternatively, a second catalyst may be provided inan interferent-eliminating layer to catalyze reactions that removeinterferents.

In certain embodiments, the sensor operates at a low oxidizingpotential, e.g., a potential of about +40 mV vs. Ag/AgCl. This sensingregion uses, for example, an osmium (Os)-based mediator constructed forlow potential operation. Accordingly, in certain embodiments the sensingelement is a redox active component that includes (1) osmium-basedmediator molecules that include (bidente) ligands, and (2) glucoseoxidase enzyme molecules. These two constituents are combined togetherin the sensing region of the sensor.

A mass transport limiting layer (not shown), e.g., an analyte fluxmodulating layer, may be included with the sensor to act as adiffusion-limiting barrier to reduce the rate of mass transport of theanalyte, for example, glucose or lactate, into the region around theworking electrodes. The mass transport limiting layers are useful inlimiting the flux of an analyte to a working electrode in anelectrochemical sensor so that the sensor is linearly responsive over alarge range of analyte concentrations and is easily calibrated. Masstransport limiting layers may include polymers and may be biocompatible.A mass transport limiting layer may provide many functions, e.g.,biocompatibility and/or interferent-eliminating functions, etc.

In certain embodiments, a mass transport limiting layer is a membranecomposed of crosslinked polymers containing heterocyclic nitrogengroups, such as polymers of polyvinylpyridine and polyvinylimidazole.Embodiments also include membranes that are made of a polyurethane, orpolyether urethane, or chemically related material, or membranes thatare made of silicone, and the like.

A membrane may be formed by crosslinking in situ a polymer, modifiedwith a zwitterionic moiety, a non-pyridine copolymer component, andoptionally another moiety that is either hydrophilic or hydrophobic,and/or has other desirable properties, in an alcohol-buffer solution.The modified polymer may be made from a precursor polymer containingheterocyclic nitrogen groups. For example, a precursor polymer may bepolyvinylpyridine or polyvinylimidazole. Optionally, hydrophilic orhydrophobic modifiers may be used to “fine-tune” the permeability of theresulting membrane to an analyte of interest. Optional hydrophilicmodifiers, such as poly(ethylene glycol), hydroxyl or polyhydroxylmodifiers, may be used to enhance the biocompatibility of the polymer orthe resulting membrane.

A membrane may be formed in situ by applying an alcohol-buffer solutionof a crosslinker and a modified polymer over an enzyme-containingsensing region and allowing the solution to cure for about one to twodays or other appropriate time period. The crosslinker-polymer solutionmay be applied to the sensing region by placing a droplet or droplets ofthe membrane solution on the sensor, by dipping the sensor into themembrane solution, by spraying the membrane solution on the sensor, andthe like. Generally, the thickness of the membrane is controlled by theconcentration of the membrane solution, by the number of droplets of themembrane solution applied, by the number of times the sensor is dippedin the membrane solution, by the volume of membrane solution sprayed onthe sensor, or by any combination of these factors. A membrane appliedin this manner may have any combination of the following functions: (1)mass transport limitation, e.g., reduction of the flux of analyte thatcan reach the sensing region, (2) biocompatibility enhancement, or (3)interferent reduction.

In some instances, the membrane may form one or more bonds with thesensing region. By bonds is meant any type of an interaction betweenatoms or molecules that allows chemical compounds to form associationswith each other, such as, but not limited to, covalent bonds, ionicbonds, dipole-dipole interactions, hydrogen bonds, London dispersionforces, and the like. For example, in situ polymerization of themembrane can form crosslinks between the polymers of the membrane andthe polymers in the sensing region. In certain embodiments, crosslinkingof the membrane to the sensing region facilitates a reduction in theoccurrence of delamination of the membrane from the sensing region.

In certain embodiments, the sensing system detects hydrogen peroxide toinfer glucose levels. For example, a hydrogen peroxide-detecting sensormay be constructed in which a sensing region includes enzyme such asglucose oxides, glucose dehydrogenase, or the like, and is positionedproximate to the working electrode. The sensing region may be covered byone or more layers, e.g., a membrane that is selectively permeable toglucose. Once the glucose passes through the membrane, it is oxidized bythe enzyme and reduced glucose oxidase can then be oxidized by reactingwith molecular oxygen to produce hydrogen peroxide.

Certain embodiments include a hydrogen peroxide-detecting sensorconstructed from a sensing region prepared by combining together, forexample: (1) a redox mediator having a transition metal complexincluding an Os polypyridyl complex with oxidation potentials of about+200 mV vs. SCE, and (2) periodate oxidized horseradish peroxidase(HRP). Such a sensor functions in a reductive mode; the workingelectrode is controlled at a potential negative to that of the Oscomplex, resulting in mediated reduction of hydrogen peroxide throughthe HRP catalyst.

In another example, a potentiometric sensor can be constructed asfollows. A glucose-sensing region is constructed by combining together(1) a redox mediator having a transition metal complex including Ospolypyridyl complexes with oxidation potentials from about −200 mV to+200 mV vs. SCE, and (2) glucose oxidase. This sensor can then be usedin a potentiometric mode, by exposing the sensor to a glucose containingsolution, under conditions of zero current flow, and allowing the ratioof reduced/oxidized Os to reach an equilibrium value. Thereduced/oxidized Os ratio varies in a reproducible way with the glucoseconcentration, and will cause the electrode's potential to vary in asimilar way.

The substrate may be formed using a variety of non-conducting materials,including, for example, polymeric or plastic materials and ceramicmaterials. Suitable materials for a particular sensor may be determined,at least in part, based on the desired use of the sensor and propertiesof the materials.

In some embodiments, the substrate is flexible. For example, if thesensor is configured for implantation into a user, then the sensor maybe made flexible (although rigid sensors may also be used forimplantable sensors) to reduce pain to the user and damage to the tissuecaused by the implantation of and/or the wearing of the sensor. Aflexible substrate often increases the user's comfort and allows a widerrange of activities. Suitable materials for a flexible substrateinclude, for example, non-conducting plastic or polymeric materials andother non-conducting, flexible, deformable materials. Examples of usefulplastic or polymeric materials include thermoplastics such aspolycarbonates, polyesters (e.g., Mylar™ and polyethylene terephthalate(PET)), polyvinyl chloride (PVC), polyurethanes, polyethers, polyamides,polyimides, or copolymers of these thermoplastics, such as PETG(glycol-modified polyethylene terephthalate).

In other embodiments, the sensors are made using a relatively rigidsubstrate to, for example, provide structural support against bending orbreaking. Examples of rigid materials that may be used as the substrateinclude poorly conducting ceramics, such as aluminum oxide and silicondioxide. An implantable sensor having a rigid substrate may have a sharppoint and/or a sharp edge to aid in implantation of a sensor without anadditional insertion device.

It will be appreciated that for many sensors and sensor applications,both rigid and flexible sensors will operate adequately. The flexibilityof the sensor may also be controlled and varied along a continuum bychanging, for example, the composition and/or thickness of thesubstrate.

In addition to considerations regarding flexibility, it is oftendesirable that implantable sensors should have a substrate which isphysiologically harmless, for example, a substrate approved by aregulatory agency or private institution for in vivo use.

The sensor may include optional features to facilitate insertion of animplantable sensor. For example, the sensor may be pointed at the tip toease insertion. In addition, the sensor may include a barb which assistsin anchoring the sensor within the tissue of the user during operationof the sensor. However, the barb is typically small enough so thatlittle damage is caused to the subcutaneous tissue when the sensor isremoved for replacement.

An implantable sensor may also, optionally, have an anticlotting agentdisposed on a portion of the substrate which is implanted into a user.This anticlotting agent may reduce or eliminate the clotting of blood orother body fluid around the sensor, particularly after insertion of thesensor. Blood clots may foul the sensor or irreproducibly reduce theamount of analyte which diffuses into the sensor. Examples of usefulanticlotting agents include heparin and tissue plasminogen activator(TPA), as well as other known anticlotting agents.

The anticlotting agent may be applied to at least a portion of that partof the sensor that is to be implanted. The anticlotting agent may beapplied, for example, by bath, spraying, brushing, or dipping, etc. Theanticlotting agent is allowed to dry on the sensor. The anticlottingagent may be immobilized on the surface of the sensor or it may beallowed to diffuse away from the sensor surface. The quantities ofanticlotting agent disposed on the sensor may be below the amountstypically used for treatment of medical conditions involving blood clotsand, therefore, have only a limited, localized effect.

FIG. 11 shows an example in vivo-based analyte monitoring system 1100 inaccordance with certain embodiments of the present disclosure. As shown,analyte monitoring system 1100 includes on body electronics 1110electrically coupled to in vivo analyte sensor 1101 (a proximal portionof which is shown in FIG. 11 ) and attached to adhesive layer 1140 forattachment on a skin surface on the body of a user. On body electronics1110 includes on body housing 1119 that defines an interior compartment.Also shown in FIG. 11 is insertion device 1150 that, when operated,transcutaneously positions a portion of analyte sensor 1101 through askin surface and in fluid contact with bodily fluid, and positions onbody electronics 1110 and adhesive layer 1140 on a skin surface. Incertain embodiments, on body electronics 1110, analyte sensor 1101 andadhesive layer 1140 are sealed within the housing of insertion device1150 before use, and in certain embodiments, adhesive layer 1140 is alsosealed within the housing or itself provides a terminal seal of theinsertion device 1150.

Referring back to the FIG. 11 , analyte monitoring system 1100 includesdisplay device 1120 which includes a display 1122 to output informationto the user, an input component 1121 such as a button, actuator, a touchsensitive switch, a capacitive switch, pressure sensitive switch, jogwheel or the like, to input data or command to display device 1120 orotherwise control the operation of display device 1120. It is noted thatsome embodiments may include display-less devices or devices without anyuser interface components. These devices may be functionalized to storedata as a data logger and/or provide a conduit to transfer data from onbody electronics and/or a display-less device to another device and/orlocation. Embodiments will be described herein as display devices forexample purposes which are in no way intended to limit the embodimentsof the present disclosure. It will be apparent that display-less devicesmay also be used in certain embodiments.

In certain embodiments, on body electronics 1110 may be configured tostore some or all of the monitored analyte related data received fromanalyte sensor 1101 in a memory during the monitoring time period, andmaintain it in memory until the usage period ends. In such embodiments,stored data is retrieved from on body electronics 1110 at the conclusionof the monitoring time period, for example, after removing analytesensor 1101 from the user by detaching on body electronics 1110 from theskin surface where it was positioned during the monitoring time period.In such data logging configurations, real time monitored analyte levelis not communicated to display device 1120 during the monitoring periodor otherwise transmitted from on body electronics 1110, but rather,retrieved from on body electronics 1110 after the monitoring timeperiod.

In certain embodiments, input component 1121 of display device 1120 mayinclude a microphone and display device 1120 may include softwareconfigured to analyze audio input received from the microphone, suchthat functions and operation of the display device 1120 may becontrolled by voice commands. In certain embodiments, an outputcomponent of display device 1120 includes a speaker for outputtinginformation as audible signals. Similar voice responsive components suchas a speaker, microphone and software routines to generate, process andstore voice driven signals may be provided to on body electronics 1110.

In certain embodiments, display 1122 and input component 1121 may beintegrated into a single component, for example a display that candetect the presence and location of a physical contact touch upon thedisplay such as a touch screen user interface. In such embodiments, theuser may control the operation of display device 1120 by utilizing a setof preprogrammed motion commands, including, but not limited to, singleor double tapping the display, dragging a finger or instrument acrossthe display, motioning multiple fingers or instruments toward oneanother, motioning multiple fingers or instruments away from oneanother, etc. In certain embodiments, a display includes a touch screenhaving areas of pixels with single or dual function capacitive elementsthat serve as LCD elements and touch sensors.

Display device 1120 also includes data communication port 1123 for wireddata communication with external devices such as remote terminal(personal computer) 1170, for example. Example embodiments of the datacommunication port 1123 include USB port, mini USB port, RS-232 port,Ethernet port, Firewire port, or other similar data communication portsconfigured to connect to the compatible data cables. Display device 1120may also include an integrated in vitro glucose meter, including invitro test strip port 1124 to receive an in vitro glucose test strip forperforming in vitro blood glucose measurements.

Referring still to FIG. 11 , display 1122 in certain embodiments isconfigured to display a variety of information—some or all of which maybe displayed at the same or different time on display 1122. In certainembodiments, the displayed information is user-selectable so that a usercan customize the information shown on a given display screen. Display1122 may include but is not limited to graphical display 1138, forexample, providing a graphical output of glucose values over a monitoredtime period (which may show important markers such as meals, exercise,sleep, heart rate, blood pressure, etc.), numerical display 1132, forexample, providing monitored glucose values (acquired or received inresponse to the request for the information), and trend or directionalarrow display 1131 that indicates a rate of analyte change and/or a rateof the rate of analyte change.

As further shown in FIG. 11 , display 1122 may also include date display1135 providing for example, date information for the user, time of dayinformation display 1139 providing time of day information to the user,battery level indicator display 1133 which graphically shows thecondition of the battery (rechargeable or disposable) of the displaydevice 1120, sensor calibration status icon display 1134 for example, inmonitoring systems that require periodic, routine or a predeterminednumber of user calibration events, notifying the user that the analytesensor calibration is necessary, audio/vibratory settings icon display1136 for displaying the status of the audio/vibratory output or alarmstate, and wireless connectivity status icon display 1137 that providesindication of wireless communication connection with other devices suchas on body electronics, data processing module 1160, and/or remoteterminal 1170. As additionally shown in FIG. 11 , display 1122 mayfurther include simulated touch screen buttons 1140, 1141 for accessingmenus, changing display graph output configurations or otherwise forcontrolling the operation of display device 1120.

Referring back to FIG. 11 , in certain embodiments, display 1122 ofdisplay device 1120 may be additionally, or instead of visual display,configured to output alarms notifications such as alarm and/or alertnotifications, glucose values etc., which may be audible, tactile, orany combination thereof. In one aspect, the display device 1120 mayinclude other output components such as a speaker, vibratory outputcomponent and the like to provide audible and/or vibratory outputindication to the user in addition to the visual output indicationprovided on display 1122.

After the positioning of on body electronics 1110 on the skin surfaceand analyte sensor 1101 in vivo to establish fluid contact withinterstitial fluid (or other appropriate bodily fluid), on bodyelectronics 1110 in certain embodiments is configured to wirelesslycommunicate analyte related data (such as, for example, datacorresponding to monitored analyte level and/or monitored temperaturedata, and/or stored historical analyte related data) when on bodyelectronics 1110 receives a command or request signal from displaydevice 1120. In certain embodiments, on body electronics 1110 may beconfigured to at least periodically broadcast real time data associatedwith monitored analyte level which is received by display device 1120when display device 1120 is within communication range of the databroadcast from on body electronics 1110, e.g., it does not need acommand or request from a display device to send information.

For example, display device 1120 may be configured to transmit one ormore commands to on body electronics 1110 to initiate data transfer, andin response, on body electronics 1110 may be configured to wirelesslytransmit stored analyte related data collected during the monitoringtime period to display device 1120. Display device 1120 may in turn beconnected to a remote terminal 1170 such as a personal computer andfunctions as a data conduit to transfer the stored analyte levelinformation from the on body electronics 1110 to remote terminal 1170.In certain embodiments, the received data from the on body electronics1110 may be stored (permanently or temporarily) in one or more memory ofthe display device 1120. In certain other embodiments, display device1120 is configured as a data conduit to pass the data received from onbody electronics 1110 to remote terminal 1170 that is connected todisplay device 1120.

Referring still to FIG. 11 , also shown in analyte monitoring system1100 are data processing module 1160 and remote terminal 1170. Remoteterminal 1170 may include a personal computer, a server terminal alaptop computer or other suitable data processing devices includingsoftware for data management and analysis and communication with thecomponents in the analyte monitoring system 1100. For example, remoteterminal 1170 may be connected to a local area network (LAN), a widearea network (WAN), or other data network for uni-directional orbi-directional data communication between remote terminal 1170 anddisplay device 1120 and/or data processing module 1160.

Remote terminal 1170 in certain embodiments may include one or morecomputer terminals located at a physician's office or a hospital. Forexample, remote terminal 1170 may be located at a location other thanthe location of display device 1120. Remote terminal 1170 and displaydevice 1120 could be in different rooms or different buildings. Remoteterminal 1170 and display device 1120 could be at least about one mileapart, e.g., at least about 10 miles apart, e.g., at least about 1100miles apart. For example, remote terminal 1170 could be in the same cityas display device 1120, remote terminal 1170 could be in a differentcity than display device 1120, remote terminal 1170 could be in the samestate as display device 1120, remote terminal 1170 could be in adifferent state than display device 1120, remote terminal 1170 could bein the same country as display device 1120, or remote terminal 1170could be in a different country than display device 1120, for example.

In certain embodiments, a separate, optional datacommunication/processing device such as data processing module 1160 maybe provided in analyte monitoring system 1100. Data processing module1160 may include components to communicate using one or more wirelesscommunication protocols such as, for example, but not limited to,infrared (IR) protocol, Bluetooth protocol, Zigbee protocol, and 802.11wireless LAN protocol. Additional description of communication protocolsincluding those based on Bluetooth protocol and/or Zigbee protocol canbe found in U.S. Patent Publication No. 2006/0193375 incorporated hereinby reference in its entirety for all purposes. Data processing module1160 may further include communication ports, drivers or connectors toestablish wired communication with one or more of display device 1120,on body electronics 1110, or remote terminal 1170 including, forexample, but not limited to USB connector and/or USB port, Ethernetconnector and/or port, FireWire connector and/or port, or RS-232 portand/or connector.

In certain embodiments, data processing module 1160 is programmed totransmit a polling or query signal to on body electronics 1110 at apredetermined time interval (e.g., once every minute, once every fiveminutes, or the like), and in response, receive the monitored analytelevel information from on body electronics 1110. Data processing module1160 stores in its memory the received analyte level information, and/orrelays or retransmits the received information to another device such asdisplay device 1120. More specifically in certain embodiments, dataprocessing module 1160 may be configured as a data relay device toretransmit or pass through the received analyte level data from on bodyelectronics 1110 to display device 1120 or a remote terminal (forexample, over a data network such as a cellular or WiFi data network) orboth.

In certain embodiments, on body electronics 1110 and data processingmodule 1160 may be positioned on the skin surface of the user within apredetermined distance of each other (for example, about 1-12 inches, orabout 1-10 inches, or about 1-7 inches, or about 1-5 inches) such thatperiodic communication between on body electronics 1110 and dataprocessing module 1160 is maintained. Alternatively, data processingmodule 1160 may be worn on a belt or clothing item of the user, suchthat the desired distance for communication between the on bodyelectronics 1110 and data processing module 1160 for data communicationis maintained. In a further aspect, the housing of data processingmodule 1160 may be configured to couple to or engage with on bodyelectronics 1110 such that the two devices are combined or integrated asa single assembly and positioned on the skin surface. In furtherembodiments, data processing module 1160 is detachably engaged orconnected to on body electronics 1110 providing additional modularitysuch that data processing module 1160 may be optionally removed orreattached as desired.

Referring again to FIG. 11 , in certain embodiments, data processingmodule 1160 is programmed to transmit a command or signal to on bodyelectronics 1110 at a predetermined time interval such as once everyminute, or once every 5 minutes or once every 30 minutes or any othersuitable or desired programmable time interval to request analyterelated data from on body electronics 1110. When data processing module1160 receives the requested analyte related data, it stores the receiveddata. In this manner, analyte monitoring system 1100 may be configuredto receive the continuously monitored analyte related information at theprogrammed or programmable time interval, which is stored and/ordisplayed to the user. The stored data in data processing module 1160may be subsequently provided or transmitted to display device 1120,remote terminal 1170 or the like for subsequent data analysis such asidentifying frequency of periods of glycemic level excursions over themonitored time period, or the frequency of the alarm event occurrenceduring the monitored time period, for example, to improve therapyrelated decisions. Using this information, the doctor, healthcareprovider or the user may adjust or recommend modification to the diet,daily habits and routines such as exercise, and the like.

In another embodiment, data processing module 1160 transmits a commandor signal to on body electronics 1110 to receive the analyte relateddata in response to a user activation of a switch provided on dataprocessing module 1160 or a user initiated command received from displaydevice 1120. In further embodiments, data processing module 1160 isconfigured to transmit a command or signal to on body electronics 1110in response to receiving a user initiated command only after apredetermined time interval has elapsed. For example, in certainembodiments, if the user does not initiate communication within aprogrammed time period, such as, for example about 5 hours from lastcommunication (or 10 hours from the last communication, or 24 hours fromthe last communication), the data processing module 1160 may beprogrammed to automatically transmit a request command or signal to onbody electronics 1110. Alternatively, data processing module 1160 may beprogrammed to activate an alarm to notify the user that a predeterminedtime period of time has elapsed since the last communication between thedata processing module 1160 and on body electronics 1110. In thismanner, users or healthcare providers may program or configure dataprocessing module 1160 to provide certain compliance with analytemonitoring regimen, so that frequent determination of analyte levels ismaintained or performed by the user.

In certain embodiments, when a programmed or programmable alarmcondition is detected (for example, a detected glucose level monitoredby analyte sensor 1101 that is outside a predetermined acceptable rangeindicating a physiological condition which requires attention orintervention for medical treatment or analysis (for example, ahypoglycemic condition, a hyperglycemic condition, an impendinghyperglycemic condition or an impending hypoglycemic condition), the oneor more output indications may be generated by the control logic orprocessor of the on body electronics 1110 and output to the user on auser interface of on body electronics 1110 so that corrective action maybe timely taken. In addition to or alternatively, if display device 1120is within communication range, the output indications or alarm data maybe communicated to display device 1120 whose processor, upon detectionof the alarm data reception, controls the display 1122 to output one ormore notification.

In certain embodiments, control logic or processors of on bodyelectronics 1110 can execute software programs stored in memory todetermine future or anticipated analyte levels based on informationobtained from analyte sensor 1101, e.g., the current analyte level, therate of change of the analyte level, the acceleration of the analytelevel change, and/or analyte trend information determined based onstored monitored analyte data providing a historical trend or directionof analyte level fluctuation as function time during monitored timeperiod. Predictive alarm parameters may be programmed or programmable indisplay device 1120, or the on body electronics 1110, or both, andoutput to the user in advance of anticipating the user's analyte levelreaching the future level. This provides the user an opportunity to taketimely corrective action.

Information, such as variation or fluctuation of the monitored analytelevel as a function of time over the monitored time period providinganalyte trend information, for example, may be determined by one or morecontrol logic or processors of display device 1120, data processingmodule 1160, and/or remote terminal 1170, and/or on body electronics1110. Such information may be displayed as, for example, a graph (suchas a line graph) to indicate to the user the current and/or historicaland/or and predicted future analyte levels as measured and predicted bythe analyte monitoring system 1100. Such information may also bedisplayed as directional arrows (for example, see trend or directionalarrow display 1131) or other icon(s), e.g., the position of which on thescreen relative to a reference point indicated whether the analyte levelis increasing or decreasing as well as the acceleration or decelerationof the increase or decrease in analyte level. This information may beutilized by the user to determine any necessary corrective actions toensure the analyte level remains within an acceptable and/or clinicallysafe range. Other visual indicators, including colors, flashing, fading,etc., as well as audio indicators including a change in pitch, volume,or tone of an audio output and/or vibratory or other tactile indicatorsmay also be incorporated into the display of trend data as means ofnotifying the user of the current level and/or direction and/or rate ofchange of the monitored analyte level. For example, based on adetermined rate of glucose change, programmed clinically significantglucose threshold levels (e.g., hyperglycemic and/or hypoglycemiclevels), and current analyte level derived by an in vivo analyte sensor,the system 1100 may include an algorithm stored on computer readablemedium to determine the time it will take to reach a clinicallysignificant level and will output notification in advance of reachingthe clinically significant level, e.g., 30 minutes before a clinicallysignificant level is anticipated, and/or 20 minutes, and/or 10 minutes,and/or 5 minutes, and/or 3 minutes, and/or 1 minute, and so on, withoutputs increasing in intensity or the like.

Referring again back to FIG. 11 , in certain embodiments, softwarealgorithm(s) for execution by data processing module 1160 may be storedin an external memory device such as an SD card, microSD card, compactflash card, XD card, Memory Stick card, Memory Stick Duo card, or USBmemory stick/device including executable programs stored in such devicesfor execution upon connection to the respective one or more of the onbody electronics 1110, remote terminal 1170 or display device 1120. In afurther aspect, software algorithms for execution by data processingmodule 1160 may be provided to a communication device such as a mobiletelephone including, for example, WiFi or Internet enabled smart phonesor personal digital assistants (PDAs) as a downloadable application forexecution by the downloading communication device.

Examples of smart phones include Windows®, Android™, iPhone® operatingsystem, Palm® WebOS™, Blackberry® operating system, or Symbian®operating system based mobile telephones with data network connectivityfunctionality for data communication over an internet connection and/ora local area network (LAN). PDAs as described above include, forexample, portable electronic devices including one or more processorsand data communication capability with a user interface (e.g.,display/output unit and/or input unit, and configured for performingdata processing, data upload/download over the internet, for example. Insuch embodiments, remote terminal 1170 may be configured to provide theexecutable application software to the one or more of the communicationdevices described above when communication between the remote terminal1170 and the devices are established.

On Body Electronics

In certain embodiments, on body electronics (or sensor control device)1110 (FIG. 11 ) includes at least a portion of the electronic componentsthat operate the sensor and the display device. The electroniccomponents of the on body electronics typically include a power supplyfor operating the on body electronics and the sensor, a sensor circuitfor obtaining signals from and operating the sensor, a measurementcircuit that converts sensor signals to a desired format, and aprocessing circuit (or processing circuitry) that, at minimum, obtainssignals from the sensor circuit and/or measurement circuit and providesthe signals to an optional on body electronics. In some embodiments, theprocessing circuit may also partially or completely evaluate the signalsfrom the sensor and convey the resulting data to the optional on bodyelectronics and/or activate an optional alarm system if the analytelevel exceeds a threshold. The processing circuit often includes digitallogic circuitry.

The on body electronics may optionally contain electronics fortransmitting the sensor signals or processed data from the processingcircuit to a receiver/display unit; a data storage unit for temporarilyor permanently storing data from the processing circuit; a temperatureprobe circuit for receiving signals from and operating a temperatureprobe; a reference voltage generator for providing a reference voltagefor comparison with sensor-generated signals; and/or a watchdog circuitthat monitors the operation of the electronic components in the on bodyelectronics.

Moreover, the on body electronics may also include digital and/or analogcomponents utilizing semiconductor devices, including transistors. Tooperate these semiconductor devices, the on body electronics may includeother components including, for example, a bias control generator tocorrectly bias analog and digital semiconductor devices, an oscillatorto provide a clock signal, and a digital logic and timing component toprovide timing signals and logic operations for the digital componentsof the circuit.

As an example of the operation of these components, the sensor circuitand the optional temperature probe circuit provide raw signals from thesensor to the measurement circuit. The measurement circuit converts theraw signals to a desired format, using for example, a current-to-voltageconverter, current-to-frequency converter, and/or a binary counter orother indicator that produces a signal proportional to the absolutevalue of the raw signal. This may be used, for example, to convert theraw signal to a format that can be used by digital logic circuits. Theprocessing circuit may then, optionally, evaluate the data and providecommands to operate the electronics.

FIG. 12 is a block diagram of the on body electronics 1110 (FIG. 11 ) incertain embodiments. Referring to FIG. 12 , on body electronics 1110 incertain embodiments includes a control unit 1210 (such as, for examplebut not limited to, one or more processors (or processing circuitry)and/or ASICs with processing circuitry), operatively coupled to analogfront end circuitry 1270 to process signals such as raw current signalsreceived from analyte sensor 1101. Also shown in FIG. 12 is memory 1220operatively coupled to control unit 1210 for storing data and/orsoftware routines for execution by control unit 1210. Memory 1220 incertain embodiments may include electrically erasable programmable readonly memory (EEPROM), erasable programmable read only memory (EPROM),random access memory (RAM), read only memory (ROM), flash memory, or oneor more combinations thereof.

In certain embodiments, control unit 1210 accesses data or softwareroutines stored in the memory 1220 to update, store or replace storeddata or information in the memory 1220, in addition to retrieving one ormore stored software routines for execution. Also shown in FIG. 12 ispower supply 1260 which, in certain embodiments, provides power to someor all of the components of on body electronics 1110. For example, incertain embodiments, power supply 1260 is configured to provide power tothe components of on body electronics 1110 except for communicationmodule 1240. In such embodiments, on body electronics 1110 is configuredto operate analyte sensor 1101 to detect and monitor the analyte levelat a predetermined or programmed (or programmable) time intervals, andgenerating and storing, for example, the signals or data correspondingto the detected analyte levels.

In certain embodiments, power supply 1260 in on body electronics 1110may be toggled between its internal power source (e.g., a battery) andthe RF power received from display device 1120. For example, in certainembodiments, on body electronics 1110 may include a diode or a switchthat is provided in the internal power source connection path in on bodyelectronics 1110 such that, when a predetermined level of RF power isdetected by on body electronics 1110, the diode or switch is triggeredto disable the internal power source connection (e.g., making an opencircuit at the power source connection path), and the components of onbody electronics is powered with the received RF power. The open circuitat the power source connection path prevents the internal power sourcefrom draining or dissipating as in the case when it is used to power onbody electronics 1110.

When the RF power from display device 1120 falls below the predeterminedlevel, the diode or switch is triggered to establish the connectionbetween the internal power source and the other components of on bodyelectronics 1110 to power the on body electronics 1110 with the internalpower source. In this manner, in certain embodiments, toggling betweenthe internal power source and the RF power from display device 1120 maybe configured to prolong or extend the useful life of the internal powersource.

The stored analyte related data, however, is not transmitted orotherwise communicated to another device such as display device 1120(FIG. 11 ) until communication module 1240 is separately powered, forexample, with the RF power from display device 1120 that is positionedwithin a predetermined distance from on body electronics 1110. In suchembodiments, analyte level is sampled based on the predetermined orprogrammed time intervals as discussed above, and stored in memory 1220.When analyte level information is requested, for example, based on arequest or transmit command received from another device such as displaydevice 1120 (FIG. 11 ), using the RF power from the display device,communication module 1240 of on body electronics 1110 initiates datatransfer to the display device 1120.

Referring back to FIG. 12 , an optional output unit 1250 is provided toon body electronics 1110. In certain embodiments, output unit 1250 mayinclude an LED indicator, for example, to alert the user of one or morepredetermined conditions associated with the operation of the on bodyelectronics 1110 and/or the determined analyte level. By way ofnonlimiting example, the on body electronics 1110 may be programmed toassert a notification using an LED indicator, or other indicator on theon body electronics 1110 when signals (based on one sampled sensor datapoint, or multiple sensor data points) received from analyte sensor 1101are indicated to be beyond a programmed acceptable range, potentiallyindicating a health risk condition such as hyperglycemia orhypoglycemia, or the onset or potential of such conditions. With suchprompt or indication, the user may be timely informed of such potentialcondition, and using display device 1120, acquire the glucose levelinformation from the on body electronics 1110 to confirm the presence ofsuch conditions so that timely corrective actions may be taken.

Referring again to FIG. 12 , antenna 1230 and communication module 1240operatively coupled to the control unit 1210 may be configured to detectand process the RF power when on body electronics 1110 is positionedwithin predetermined proximity to the display device 1120 (FIG. 11 )that is providing or radiating the RF power. Further, on bodyelectronics 1110 may provide analyte level information and optionallyanalyte trend or historical information based on stored analyte leveldata, to display device 1120. In certain aspects, the trend informationmay include a plurality of analyte level information over apredetermined time period that are stored in the memory 1220 of the onbody electronics 1110 and provided to the display device 1120 with thereal time analyte level information. For example, the trend informationmay include a series of time spaced analyte level data for the timeperiod since the last transmission of the analyte level information tothe display device 1120. Alternatively, the trend information mayinclude analyte level data for the prior 30 minutes or one hour that arestored in memory 1220 and retrieved under the control of the controlunit 1210 for transmission to the display device 1120.

In certain embodiments, on body electronics 1110 is configured to storeanalyte level data in first and second FIFO buffers that are part ofmemory 1220. The first FIFO buffer stores 16 (or 10 or 20) of the mostrecent analyte level data spaced one minute apart. The second FIFObuffer stores the most recent 8 hours (or 10 hours or 3 hours) ofanalyte level data spaced 10 minutes (or 15 minutes or 20 minutes). Thestored analyte level data are transmitted from on body electronics 1110to display unit 1120 in response to a request received from display unit1120. Display unit 1120 uses the analyte level data from the first FIFObuffer to estimate glucose rate-of-change and analyte level data fromthe second FIFO buffer to determine historical plots or trendinformation.

In certain embodiments, for configurations of the on body electronicsthat includes a power supply, the on body electronics may be configuredto detect an RF control command (ping signal) from the display device1120. More specifically, an On/Off Key (OOK) detector may be provided inthe on body electronics which is turned on and powered by the powersupply of the on body electronics to detect the RF control command orthe ping signal from the display device 1120. Additional details of theOOK detector are provided in U.S. Patent Publication No. 2008/0278333,the disclosure of which is incorporated by reference in its entirety forall purposes. In certain aspects, when the RF control command isdetected, on body electronics determines what response packet isnecessary, and generates the response packet for transmission back tothe display device 1120. In this embodiment, the analyte sensor 1101continuously receives power from the power supply or the battery of theon body electronics and operates to monitor the analyte levelcontinuously in use. However, the sampled signal from the analyte sensor1101 may not be provided to the display device 1120 until the on bodyelectronics receives the RF power (from the display device 1120) toinitiate the transmission of the data to the display device 1120. In oneembodiment, the power supply of the on body electronics may include arechargeable battery which charges when the on body electronics receivesthe RF power (from the display device 1120, for example).

Referring back to FIG. 11 , in certain embodiments, on body electronics1110 and the display device 1120 may be configured to communicate usingRFID (radio frequency identification) protocols. More particularly, incertain embodiments, the display device 1120 is configured tointerrogate the on body electronics 1110 (associated with an RFID tag)over an RF communication link, and in response to the RF interrogationsignal from the display device 1120, on body electronics 1110 providesan RF response signal including, for example, data associated with thesampled analyte level from the sensor 1101. Additional informationregarding the operation of RFID communication can be found in U.S. Pat.No. 7,545,272, and in U.S. application Ser. Nos. 12/698,624, 12/699,653,12/761,387, and U.S. Patent Publication No. 2009/0108992 the disclosuresof all of which are incorporated herein by reference in their entiretiesand for all purposes.

For example, in one embodiment, the display device 1120 may include abackscatter RFID reader configured to provide an RF field such that whenon body electronics 1110 is within the transmitted RF field of the RFIDreader, on body electronics 1110 antenna is tuned and in turn provides areflected or response signal (for example, a backscatter signal) to thedisplay device 1120. The reflected or response signal may includesampled analyte level data from the analyte sensor 1101.

In certain embodiments, when display device 1120 is positioned in withina predetermined range of the on body electronics 1110 and receives theresponse signal from the on body electronics 1110, the display device1120 is configured to output an indication (audible, visual orotherwise) to confirm the analyte level measurement acquisition. Thatis, during the course of the 5 to 10 days of wearing the on bodyelectronics 1110, the user may at any time position the display device1120 within a predetermined distance (for example, about 1-5 inches, orabout 1-10 inches, or about 1-12 inches) from on body electronics 1110,and after waiting a few seconds of sample acquisition time period, anaudible indication is output confirming the receipt of the real timeanalyte level information. The received analyte information may beoutput to the display 1122 (FIG. 11 ) of the display device 1120 forpresentation to the user.

Display Devices

FIG. 13 is a block diagram of display device 1120 as shown in FIG. 11 incertain embodiments. Although the term display device is used, thedevice can be configured to read without displaying data, and can beprovided without a display, such as can be the case with a relay orother device that relays a received signal according to the same or adifferent transmission protocol (e.g., NFC-to-Bluetooth or Bluetooth LowEnergy). Referring to FIG. 13 , display device 1120 (FIG. 11 ) includescontrol unit 1310, such as one or more processors (or processingcircuitry) operatively coupled to a display 1122, and an input component(e.g., user interface) 1121. The display device 1120 may also includeone or more data communication ports such as USB port (or connector)1123 or RS-232 port 1330 (or any other wired communication ports) fordata communication with a data processing module 1160 (FIG. 11 ), remoteterminal 1170 (FIG. 11 ), or other devices such as a personal computer,a server, a mobile computing device, a mobile telephone, a pager, orother handheld data processing devices including mobile telephones suchas internet connectivity enabled smart phones, with data communicationand processing capabilities including data storage and output.

Referring back to FIG. 13 , display device 1120 may include a strip port1124 configured to receive in vitro test strips, the strip port 1124coupled to the control unit 1310, and further, where the control unit1310 includes programming to process the sample on the in vitro teststrip which is received in the strip port 1124. Any suitable in vitrotest strip may be employed, e.g., test strips that only require a verysmall amount (e.g., one microliter or less, e.g., about 0.5 microliteror less, e.g., about 0.1 microliter or less), of applied sample to thestrip in order to obtain accurate glucose information. Display deviceswith integrated in vitro monitors and test strip ports may be configuredto conduct in vitro analyte monitoring with no user calibration of thein vitro test strips (e.g., no human intervention calibration).

In certain embodiments, an integrated in vitro meter can accept andprocess a variety of different types of test strips (e.g., those thatrequire user calibration and those that do not), some of which may usedifferent technologies (those that operate using amperometric techniquesand those that operate using coulometric techniques), etc. Detaileddescription of such test strips and devices for conducting in vitroanalyte monitoring is provided in U.S. Pat. Nos. 6,377,894, 6,616,819,7,749,740, 7,418,285; U.S. Patent Publication Nos. 2004/0118704,2006/0096006, 2008/0066305, 2008/0267823, 2010/0094610, 2010/0094111,and 2010/0094112, and U.S. application Ser. No. 12/695,947, thedisclosures of all of which are incorporated herein by reference intheir entireties and for all purposes.

Glucose information obtained by the in vitro glucose testing device maybe used for a variety of purposes. For example, the information may beused to calibrate analyte sensor 1101 (FIG. 11 ) if the sensor requiresin vivo calibration, confirm results of analyte sensor 1101 to increasethe confidence in the results from sensor 1101 indicating the monitoredanalyte level (e.g., in instances in which information obtained bysensor 1101 is employed in therapy related decisions), etc. In certainembodiments, analyte sensors do not require calibration by humanintervention during its usage life. However, in certain embodiments, asystem may be programmed to self-detect problems and take action, e.g.,shut off and/or notify a user. For example, an analyte monitoring systemmay be configured to detect system malfunction, or potential degradationof sensor stability or potential adverse condition associated with theoperation of the analyte sensor, the system may notify the user, usingdisplay device 1120 (FIG. 11 ) for example, to perform analyte sensorcalibration or compare the results received from the analyte sensorcorresponding to the monitored analyte level, to a reference value (suchas a result from an in vitro blood glucose measurement).

In certain embodiments, when the potential adverse condition associatedwith the operation of the sensor, and/or potential sensor stabilitydegradation condition is detected, the system may be configured to shutdown (automatically without notification to the user, or after notifyingthe user) or disable the output or display of the monitored analytelevel information received the on body electronics assembly. In certainembodiments, the analyte monitoring system may be shut down or disabledtemporarily to provide an opportunity to the user to correct anydetected adverse condition or sensor instability. In certain otherembodiments, the analyte monitoring system may be permanently disabledwhen the adverse sensor operation condition or sensor instability isdetected.

Referring still to FIG. 13 , power supply 1320, such as one or morebatteries, rechargeable or single use disposable, is also provided andoperatively coupled to control unit 1310, and configured to provide thenecessary power to display device 1120 (FIG. 11 ) for operation. Inaddition, display device 1120 may include an antenna 1351 such as a 433MHz (or other equivalent) loop antenna, 13.56 MHz antenna, or a 2.45 GHzantenna, coupled to a receiver processor 1350 (which may include a 433MHz, 13.56 MHz, or 2.45 GHz transceiver chip, for example) for wirelesscommunication with the on body electronics 1110 (FIG. 11 ).Additionally, an inductive loop antenna 1341 is provided and coupled toa squarewave driver 1340 which is operatively coupled to control unit1310.

In certain embodiments, data packets received from on body electronicsand received in response to a request from display device, for example,include one or more of a current glucose level from the analyte sensor,a current estimated rate of glycemic change, and a glucose trend historybased on automatic readings acquired and stored in memory of on skinelectronics. For example, current glucose level may be output on display1122 of display device 1120 as a numerical value, the current estimatedrage of glycemic change may be output on display 1122 as a directionalarrow 1131 (FIG. 11 ), and glucose trend history based on storedmonitored values may be output on display 1122 as a graphical trace 1138(FIG. 11 ). In certain embodiments, the processor (or processingcircuitry) of display device 1120 may be programmed to output more orless information for display on display 1122, and further, the type andamount of information output on display 1122 may be programmed orprogrammable by the user.

Data Communication and Processing Routines

Referring now to FIG. 14 which illustrates data and/or commands exchangebetween on body electronics 1110 and display device 1120 during theinitialization and pairing routine, display device 1120 provides andinitial signal 1421 to on body electronics 1110. When the receivedinitial signal 1421 includes RF energy exceeding a predeterminedthreshold level 1403, an envelope detector of on body electronics 1110is triggered 1404, one or more oscillators of on body electronics 1110turns on, and control logic or processors of on body electronics 1110 istemporarily latched on to retrieve and execute one or more softwareroutines to extract the data stream from the envelope detector 1404. Ifthe data stream from the envelope detector returns a valid query 1405, areply signal 1422 is transmitted to display device 1120. The replysignal 1422 from on body electronics 1110 includes an identificationcode such as on body electronics 1110 serial number. Thereafter, the onbody electronics 1110 returns to shelf mode in an inactive state.

On the other hand, if the data stream from the envelope detector doesnot return a valid query from display device 1120, on body electronics1110 does not transmit a reply signal to display device 1120 nor is onbody electronics 1110 serial number provided to display device 1120.Thereafter, on body electronics 1110 returns to shelf mode 1403, andremains in powered down state until it detects a subsequent initialsignal 1421 from display device 1120.

When display device 1120 receives the data packet includingidentification information or serial number from on body electronics1110, it extracts that information from the data packet 1412. With theextracted on body electronics 1110 serial number, display device 1120determines whether on body electronics 1110 associated with the receivedserial number is configured. If on body electronics 1110 associated withthe received serial number has already been configured, for example, byanother display device, display device 1120 returns to the beginning ofthe routine to transmit another initial signal 1411 in an attempt toinitialize another on body electronics that has not been configured yet.In this manner, in certain embodiments, display device 1120 isconfigured to pair with an on body electronics that has not already beenpaired with or configured by another display device.

Referring back to FIG. 14 , if on body electronics 1110 associated withthe extracted serial number has not been configured 1413, display device1120 is configured to transmit a wake up signal to on body electronics1110 which includes a configure command. In certain embodiments, wake upcommand from display device 1120 includes a serial number of on bodyelectronics 1110 so that only the on body electronics with the sameserial number included in the wake up command detects and exits theinactive shelf mode and enters the active mode. More specifically, whenthe wake up command including the serial number is received by on bodyelectronics 1110, control logic or one or more processors (or processingcircuitry) of on body electronics 1110 executes routines 1403, 1404, and1405 to temporarily exit the shelf mode, when the RF energy receivedwith the wakeup signal (including the configure command) exceeds thethreshold level, and determines that it is not a valid query (as thatdetermination was previously made and its serial number transmitted todisplay device 1120). Thereafter, on body electronics 1110 determineswhether the received serial number (which was received with the wake upcommand) matches its own stored serial number 1406. If the two serialnumbers do not match, routine returns to the beginning where on bodyelectronics 1110 is again placed in inactive shelf mode 1402. On theother hand, if on body electronics 1110 determines that the receivedserial number matches its stored serial number 1406, control logic orone or more processors of on body electronics 1110 permanently latcheson 1407, and oscillators are turned on to activate on body electronics1110. Further, referring back to FIG. 14 , when on body electronics 1110determines that the received serial number matches its own serial number1406, display device 1120 and on body electronics 1110 are successfullypaired 1416.

In this manner, using a wireless signal to turn on and initialize onbody electronics 1110, the shelf life of on body electronics 1110 may beprolonged since very little current is drawn or dissipated from on bodyelectronics 1110 power supply during the time period that on bodyelectronics 1110 is in inactive, shelf mode prior to operation. Incertain embodiments, during the inactive shelf mode, on body electronics1110 has minimal operation, if any, that require extremely low current.The RF envelope detector of on body electronics 1110 may operate in twomodes—a desensitized mode where it is responsive to received signals ofless than about 1 inch, and normal operating mode with normal signalsensitivity such that it is responsive to receives signals at a distanceof about 3-12 inches.

During the initial pairing between display device 1120 and on bodyelectronics 1110, in certain embodiments, display device 1120 sends itsidentification information such as, for example, 4 bytes of displaydevice ID which may include its serial number. On body electronics 1110stores the received display device ID in one or more storage unit ormemory component and subsequently includes the stored display device IDdata in response packets or data provided to the display device 1120. Inthis manner, display device 1120 can discriminate detected data packetsfrom on body electronics 1110 to determine that the received or detecteddata packets originated from the paired or correct on body electronics1110. The pairing routine based on the display device ID in certainembodiments avoids potential collision between multiple devices,especially in the cases where on body electronics 1110 does notselectively provide the analyte related data to a particular displaydevice, but rather, provide to any display device within range and/orbroadcast the data packet to any display device in communication range.

In certain embodiments, the payload size from display device 1120 to onbody electronics 1110 is 12 bytes, which includes 4 bytes of displaydevice ID, 4 bytes of on body device ID, one byte of command data, onebyte of spare data space, and two bytes for CRC (cyclic redundancycheck) for error detection.

After pairing is complete, when display device 1120 queries on bodyelectronics 1110 for real time monitored analyte information and/orlogged or stored analyte data, in certain embodiments, the responsivedata packet transmitted to display device 1120 includes a total of 418bytes that includes 34 bytes of status information, time information andcalibration data, 96 bytes of the most recent 16 one-minute glucose datapoints, and 288 bytes of the most recent 15 minute interval glucose dataover the 12 hour period. Depending upon the size or capacity of thememory or storage unit of on body electronics 1110, data stored andsubsequently provided to the display device 1120 may have a differenttime resolution and/or span a longer or shorter time period. Forexample, with a larger data buffer, glucose related data provided to thedisplay device 1120 may include glucose data over a 24 hour time periodat 15 minute sampling intervals, 10 minute sampling intervals, 5 minutesampling intervals, or one minute sampling interval. Further, thedetermined variation in the monitored analyte level illustratinghistorical trend of the monitored analyte level may be processed and/ordetermined by the on body electronics 1110, or alternatively or inaddition to, the stored data may be provided to the display device 1120which may then determine the trend information of the monitored analytelevel based on the received data packets.

The size of the data packets provided to display device 1120 from onbody electronics 1110 may also vary depending upon the communicationprotocol and/or the underlying data transmission frequency—whether usinga 433 MHz, a 13.56 MHz, or 2.45 GHz in addition to other parameters suchas, for example, the presence of data processing devices such as aprocessor or processing circuitry (e.g., central processing unit CPU) inon body electronics 1110, in addition to the ASIC state machine, size ofthe data buffer and/or memory, and the like.

In certain embodiments, upon successful activation of on bodyelectronics 1110 and pairing with display device 1120, control unit ofdisplay device 1120 may be programmed to generate and output one or morevisual, audible and/or haptic notifications to output to the user ondisplay 1122, or on the user interface of display device 1120. Incertain embodiments, only one display device can pair with one on bodyelectronics at one time. Alternatively, in certain embodiments, onedisplay device may be configured to pair with multiple on bodyelectronics at the same time.

Once paired, display 1122 of display device 1120, for example, outputs,under the control of the processor of display device 1120, the remainingoperational life of the analyte sensor 1101 in user. Furthermore, as theend of sensor life approaches, display device may be configured tooutput notifications to alert the user of the approaching end of sensorlife. The schedule for such notification may be programmed orprogrammable by the user and executed by the processor of the displaydevice.

Referring back to FIG. 11 , in certain embodiments, analyte monitoringsystem 1100 may store the historical analyte data along with a dateand/or time stamp and/or and contemporaneous temperature measurement, inmemory, such as a memory configured as a data logger as described above.In certain embodiments, analyte data is stored at the frequency of aboutonce per minute, or about once every ten minutes, or about once an hour,etc. Data logger embodiments may store historical analyte data for apredetermined period of time, e.g., a duration specified by a physician,for example, e.g., about 1 day to about 1 month or more, e.g., about 3days or more, e.g., about 5 days or more, e.g., about 7 days or more,e.g., about 2 weeks or more, e.g., about 1 month or more.

Other durations of time may be suitable, depending on the clinicalsignificance of the data being observed. The analyte monitoring system1100 may display the analyte readings to the subject during themonitoring period. In some embodiments, no data is displayed to thesubject. Optionally, the data logger can transmit the historical analytedata to a receiving device disposed adjacent, e.g., in close proximityto the data logger. For example, a receiving device may be configured tocommunicate with the data logger using a transmission protocol operativeat low power over distances of a fraction of an inch to about severalfeet. For example, and without limitation, such close proximityprotocols include Certified Wireless USB™ TransferJet™, Bluetooth® (IEEE802.15.1), WiFi™ (IEEE 802.11), ZigBee® (IEEE 802.15.4-2006), Wibree™,or the like.

The analyte data parameters may be computed by a processor or processingcircuitry executing a program stored in a memory. In certainembodiments, the processor executing the program stored in the memory isprovided in data processing module 1160 (FIG. 11 ). In certainembodiments, the processor executing the program stored in the memory isprovided in display device 1120. An example technique for analyzing datais the applied ambulatory glucose profile (AGP) analysis technique.Additional detailed descriptions are provided in U.S. Pat. Nos.5,264,104; 5,262,305; 5,320,715; 5,593,852; 6,175,752; 6,650,471; 6,746,582, 6,284,478, 7,299,082, and in U.S. patent application Ser. Nos.10/745,878; 11/060,365, the disclosures of all of which are incorporatedherein by reference in their entireties for all purposes.

As described above, in certain aspects of the present disclosure,discrete glucose measurement data may be acquired on-demand or uponrequest from the display device, where the glucose measurement isobtained from an in vivo glucose sensor transcutaneously positionedunder the skin layer of a user, and further having a portion of thesensor maintained in fluid contact with the bodily fluid under the skinlayer. Accordingly, in aspects of the present disclosure, the user ofthe analyte monitoring system may conveniently determine real timeglucose information at any time, using the RFID communication protocolas described above.

In one aspect, the integrated assembly including the on body electronicsand the insertion device may be sterilized and packaged as one singledevice and provided to the user. Furthermore, during manufacturing, theinsertion device assembly may be terminal packaged providing costsavings and avoiding the use of, for example, costly thermoformed trayor foil seal. In addition, the insertion device may include an end capthat is rotatably coupled to the insertion device body, and whichprovides a safe and sterile environment (and avoid the use of desiccantsfor the sensor) for the sensor provided within the insertion devicealong with the integrated assembly. Also, the insertion device sealedwith the end cap may be configured to retain the sensor within thehousing from significant movement during shipping such that the sensorposition relative to the integrated assembly and the insertion device ismaintained from manufacturing, assembly and shipping, until the deviceis ready for use by the user.

Drug Delivery Systems

The on body device and/or display device can also include or beintegrated with a drug (e.g., insulin, etc.) delivery device into asystem such that they, e.g., share a common housing. In otherembodiments the on body device, display device, and drug delivery devicecan each be separate and discrete devices, e.g., they each have theirown housing. The drug delivery device can provide a drug to counteractthe high or low level of the analyte in response to a signal from asensor of the on body device, or the system may monitor the drugconcentration to ensure that the drug remains within a desiredtherapeutic range. Examples of such drug delivery devices can includemedication pumps having a cannula that remains in the body to allowinfusion over a multi-hour or multi-day period (e.g., wearable pumps forthe delivery of basal and bolus insulin). When combined with amedication pump, the on body device or display device can include areservoir to store the drug, a pump connectable to transfer tubing, andan infusion cannula. The pump can force the drug from the reservoir,through the tubing and into the diabetic's body by way of the cannulainserted therein. Other examples of drug delivery devices that can beincluded with (or integrated with) a display device include portableinjection devices that pierce the skin only for each delivery and aresubsequently removed (e.g., insulin pens). A display device, whencombined with a portable injection device, can include an injectionneedle, a reservoir for carrying the drug, an interface for controllingthe amount of drug to be delivered, and an actuator to cause injectionto occur. The device can be used repeatedly until the drug is exhausted,at which point the combined device can be discarded, or the reservoircan be replaced with a new one, at which point the combined device canbe reused repeatedly. The needle can be replaced after each injection.

An on body device combined with a drug delivery device, or a displaydevice combined with a drug delivery device, can both function as partof a closed-loop system (e.g., an artificial pancreas system requiringno user intervention to operate) or semi-closed loop system (e.g., aninsulin loop system requiring seldom user intervention to operate, suchas to confirm changes in dose). For example, the diabetic's analytelevel can be monitored in a repeated automatic fashion by the on bodydevice, which can then communicate that monitored analyte level to thedisplay device, and the appropriate drug dosage to control thediabetic's analyte level can be automatically determined andsubsequently delivered to the diabetic's body (e.g., by the displaydevice integrated with the drug delivery device, or by communication ofthe dosage from the display device to a discrete drug delivery device).Software instructions for controlling the pump and the amount of insulindelivered can be stored in the memory of the display device and executedby the display device's processing circuitry. These instructions canalso cause calculation of drug delivery amounts and durations (e.g., abolus infusion and/or a basal infusion profile) based on the analytelevel measurements obtained directly or indirectly from the on bodydevice. In some embodiments, the on body device can determine the drugdosage and communicate that to the display device.

Example Embodiments of In Vitro Analyte Monitoring Systems

In vitro analyte monitoring systems often utilize an in vitro analytesensor in the form of a test strip or strip that has a region adaptedfor contact with a sample of a bodily fluid (e.g., blood) that has beenremoved from a living body, typically by lancing the skin with a sharpsuch that one or several drops of blood exit the skin. Such in vitrodevices can be referred to as strip-based in vitro devices. In vitroanalyte sensors can be configured to sense the same analytes describedearlier with respect to in vivo analyte sensors. Many embodiments of invitro sensors can be formed on a substrate, e.g., a substantially planarsubstrate. In certain embodiments, the in vitro sensor includes aworking electrode. A working ink may be disposed on at least a portionof the working electrode. The in vitro sensor may also include at leastone counter electrode (or counter/reference electrode) and/or at leastone reference electrode or at least one reference/counter electrode.

In certain embodiments, the in vitro sensor may include a first, secondand a third electrode as illustrated in FIGS. 15A and 15B, 16, and 17 .For example, as shown in the in vitro sensor 1510 of FIG. 15A, the firstelectrode 1511 may be closest to the sample application site 111,followed by the second electrode 1512, and third electrode 1513. The invitro sensor in FIG. 15A is depicted as having a first substrate 1530onto which the electrodes are disposed and further having an insulativelayer 1531, with a cut-out for the sample chamber 1532, disposed on theelectrodes, the cut-out exposes the electrodes in the sample chamberwhile covering other portions of the electrodes. Accordingly, within thesample chamber, the electrodes are disposed such that a sample appliedat the tip of the sensor at application site 111, contacts the firstelectrode 1511 first, then the second electrode 1512, and then the thirdelectrode 1513. The conductive trace portions of the electrodes whichconnect the electrodes to a meter are covered by the insulative layer.These in vitro sensors may have an additional layer, such as a secondsubstrate disposed over the insulative layer. The cut out in theinsulative layer and the first and second substrates defines the samplechamber. In certain embodiments, the first electrode 1511 may be acounter electrode or a reference/counter electrode, the second electrode1512 may be a working electrode, and third electrode 1513 may be atrigger electrode that indicates that sample volume sufficient foraccurate analyte measurement is present in the sample chamber.

In other embodiments, at least two of the electrodes may be in a facingconfiguration. For example, the first electrode may be on a firstsubstrate of the in vitro sensor while the second and/or the thirdelectrode may be on a second substrate of the sensor, where thearrangement of the electrode with regard to the sample application sitemay be as described above.

In other embodiments, the in vitro sensor may be as shown in FIG. 15B.In FIG. 15B, the sensor 1520 includes a first electrode 1521 on a firstsubstrate 1525; two second electrodes 1522 and 1523, for detectingsufficient filling of the sample chamber, and third electrode 1524 on asecond substrate 1526. In the assembled sensor, the first electrode 1521is a facing orientation to electrodes 1522, 1523, and 1524. In thesensor of FIG. 15B, the sample may be filled from either side entrance112 or 113. A spacer layer 1510 and 1510′ in combination with the twosubstrates 1525 and 1526 define the sample chamber. The sensor in FIG.15B includes two side entrances 112 and 113 either of which can be usedto fill the sensor with a sample. In these embodiments, the sample maycontact the first (1521) and second (1522) electrodes simultaneously andbefore the sample contacts the third electrode 1524, when the sampleenters at entrance 112. In other embodiments, the sample enters atentrance 113 and contacts electrodes 1521 and 1523 simultaneously beforecontacting electrode 1522. In certain embodiments, the second electrodesact as trigger electrodes which indicate that sample volume sufficientfor accurate analyte measurement is present in the sample chamber. Incertain embodiments, the third electrode 1524 may be a working electrodeand first electrode 1521 may be a counter electrode or areference/counter electrode.

In another embodiment, the in vitro sensor may be as shown in FIG. 16 .In this embodiment, the all electrodes are disposed on a single surfaceof the same substrate 1630. These coplanar electrodes include a counterelectrode or a counter/reference electrode 1631 disposed in wrap-aroundconfiguration with reference to the working electrode 1632. A triggerelectrode 1633 is disposed downstream to electrodes 1631 and 1632 suchthat a sample applied to the application site 123 contacts the triggerelectrode 1633 after contacting electrodes 1631 and 1632.

An embodiment of an in vitro analyte sensor with electrodes in a facingconfiguration is illustrated in FIG. 17 which shows an exploded view ofsuch a sensor. The in vitro sensor includes a working electrode 17112disposed on substrate 17124. Electrodes 17118, 17120, and 17122 aredisposed on second substrate 17128. Spacer layer 17126 (e.g., anadhesive) separates working electrode 17112 from electrodes 17118,17120, and 17122. 17118 and 17122 are trigger electrodes and 17120 maybe a silver/silver chloride combined counter/reference electrode.Substrates 17128, 17124, in combination with spacer 17126 define thesample chamber 17114. Sample chamber 17114 includes two entrances onside edges of the sensor, the entrances are marked by reference numerals17114 a and 17114 b. 17110 depicts a sample as it is filled into thesample chamber 17114. Sample chamber 17114 includes the workingelectrode 17112. The trigger electrode closest to the side where thesample has been applied indicates when the sample has started fillingthe sample chamber and the trigger electrode at the opposite side of thesample chamber indicates when the sample chamber has been filled by thesample.

The terms “working electrode”, “counter electrode”, “referenceelectrode” and “counter/reference electrode” are used herein to refer toa portion or portions of a conductive trace which are configured tofunction as a working electrode, counter electrode, reference electrode,or a counter/reference electrode, respectively. In other words, aworking electrode is that portion of a conductive trace which functionsas a working electrode as described herein, e.g., that portion of aconductive trace which is exposed to an environment containing theanalyte or analytes to be measured and not covered by an insulativelayer (such as a spacer layer, a tape, or a cover), and which, in somecases, has been modified with one or more sensing layers as describedherein. Similarly, a reference electrode is that portion of a conductivetrace which functions as a reference electrode as described herein,e.g., that portion of a conductive trace which is exposed to anenvironment containing the analyte or analytes to be measured and notcovered by an insulative layer, and which, in some cases, includes asecondary conductive layer, e.g., a Ag/AgCl layer. A counter electrodeis that portion of a conductive trace which is configured to function asa counter electrode as described herein, e.g., that portion of aconductive trace which is exposed to an environment containing theanalyte or analytes to be measured and not covered by an insulativelayer. As noted above, in some embodiments, a portion of a conductivetrace may function as either or both of a counter electrode and areference electrode.

In certain embodiments, a working ink comprising an analyte responsiveenzyme may be disposed in the sample chamber of the in vitro sensor. Incertain embodiments, a sample chamber is defined by a first substrate, asecond substrate, and a spacer layer disposed between the first andsecond substrates. The spacer layer may be shorter than the firstsubstrate and a second substrate or may include a cut-out that defines aspace between the first substrate and the second substrate. The samplechamber includes at least a portion of the working electrode and thecounter or the counter/reference electrode. In certain embodiments, theworking ink may be disposed on the working electrode (e.g., in a sensorwith a facing electrode configuration) or may be disposed on both theworking electrode and the counter or the counter/reference electrode(e.g., in a sensor with a coplanar electrode configuration). The portionof the working electrode that is exposed in the sample chamber, e.g., isnot covered with the spacer layer, defines a working region that isavailable for measuring an analyte related signal from a sample presentin the sample chamber. In certain embodiments, the working region is aworking pad covered with the working ink. In certain embodiments, theworking ink in addition to containing an analyte responsive enzyme mayalso include a redox mediator. The area of the working pad may bedependent on the area of the working electrode as well as the area ofthe working electrode not covered by the spacer layer that holds thefirst and second substrates in a spaced apart manner. The thickness ofthe working pad may be a thickness suitable for measurement of theanalyte and may be controlled during the manufacturing process.

In certain embodiments, the electrodes are connected to contact pads viaa trace. The contact pads facilitate connection of the electrodes to ameter or another device that detects the electrochemical signalgenerated by the interaction of the analyte in the sample and theanalyte specific enzyme. In general, at least a portion of theelectrodes and contact pads are not covered by the spacer layer oranother insulating layer when the trace is covered by the spacer layeror another insulating layer in the assembled sensor. In certainembodiments, the trace may be made from the same material as theelectrodes and contact pads. The resistance of the trace is dependentupon the trace area as well as the trace material.

The in vitro sensors can be configured for top-filling, tip-filling,corner-filling and/or side-filling. In some embodiments, the in vitrosensors include one or more optional fill assist structures, e.g., oneor more notches, cut-outs, indentations, and/or protrusions, whichfacilitate the collection of the fluid sample. For example, the in vitrosensor can be configured such that the proximal end of the in vitrosensor is narrower than the distal end of the sensor. In one suchembodiment, the analyte sensor includes a tapered tip at the proximalend of the in vitro sensor, e.g., the end of the in vitro sensor that isopposite from the end that engages with a meter.

The in vitro analyte sensors can be configured to include one or moreprotrusions which facilitate filling of the sensors. The one or moreprotrusions may extend from the first substrate or the second substrateor both. In some embodiments, the in vitro analyte sensors include oneor more spacers positioned with respect to protrusions such that theyprovide structural support for the protrusions. Additional fill assiststructures are described in U.S. Patent Publication No. 2008/0267823,and U.S. patent application Ser. No. 11/461,725, filed Aug. 1, 2006, thedisclosures of both of which are incorporated by reference herein intheir entireties and for all purposes.

The configuration and operation of in vitro meters is well known in theart. FIG. 18A is a perspective view depicting an example embodiment ofan in vitro analyte meter 18100. In this embodiment, the meter 18100includes a test strip slot or port 18102, a display 18104 and one ormore operational buttons 18106. Although not shown in FIG. 18A, themeter 18100 can also include component circuitry for receiving signalsthat depend on the analyte level of a fluid applied to a strip that isinserted into the slot 18102, and component circuitry for determiningthe analyte level based on the received signals. This componentcircuitry can include processing circuitry communicatively coupled withnon-transitory memory. The non-transitory memory can include one or moresoftware instructions that, when executed by the processing circuitry,cause the processing circuitry to calculate the analyte level from thesignals received from the test strip, and because the processingcircuitry to cause the display of the analyte level to the user. FIG.18B is a frontal view depicting an analyte meter 18200 with display18104 and operational buttons 18106, and also having a glucose teststrip 18202 inserted into a slot 18102 for testing a body fluid sample(e.g., blood) applied to the strip 18202.

Example Embodiments of Calibration

Biochemical sensors can be described by one or more sensingcharacteristics. A common sensing characteristic is referred to as thebiochemical sensor's sensitivity, which is a measure of the sensor'sresponsiveness to the concentration of the chemical or composition it isdesigned to detect. For electrochemical sensors, this response can be inthe form of an electrical current (amperometric) or electrical charge(coulometric). For other types of sensors, the response can be in adifferent form, such as a photonic intensity (e.g., optical light). Thesensitivity of a biochemical analyte sensor can vary depending on anumber of factors, including whether the sensor is in an in vitro stateor an in vivo state.

FIG. 19A is a graph depicting the in vitro sensitivity of anamperometric analyte sensor. The in vitro sensitivity can be obtained byin vitro testing the sensor at various analyte concentrations and thenperforming a regression (e.g., linear or non-linear) or other curvefitting on the resulting data. In this example, the analyte sensor'ssensitivity is linear, or substantially linear, and can be modeledaccording to the equation y=mx+b, where y is the sensor's electricaloutput current, x is the analyte level (or concentration), m is theslope of the sensitivity and b is the intercept of the sensitivity,where the intercept generally corresponds to a background signal (e.g.,noise). For sensors with a linear or substantially linear response, theanalyte level that corresponds to a given current can be determined fromthe slope and intercept of the sensitivity. Sensors with a non-linearsensitivity require additional information to determine the analytelevel resulting from the sensor's output current, and those of ordinaryskill in the art are familiar with manners by which to model non-linearsensitivities. In certain embodiments of in vivo sensors, the in vitrosensitivity may be the same as the in vivo sensitivity, but in otherembodiments a transfer (or conversion) function is used to translate thein vitro sensitivity into the in vivo sensitivity that is applicable tothe sensor's intended in vivo use.

Biochemical sensors of the same design undergoing the same manufacturingprocess can have different in vitro sensitivities (as well as in vivosensitivities, if applicable) due to variations in that manufacturingprocess and the materials used for fabrication. FIG. 19B depictsexamples of different sensitivities 1901-1904 for different analytesensors of the same mechanical and electrochemical design. Thesensitivities 1901-1904 in this example are linear for ease ofillustration, but in other examples can be non-linear. Here, a firstsensitivity 1901 has the same intercept as a second sensitivity 1902,but a greater slope. A third sensitivity 1903 has generally the sameslope as that of sensitivity 1902, but a greater intercept. A fourthsensitivity 1904 has a still greater slope and intercept that those ofsensitivities 1901-1903.

In order to compensate for these variations, the sensor can becalibrated. Calibration is a technique for improving or maintainingaccuracy by adjusting a sensor's measured output to reduce thedifferences with the sensor's expected output. One or more parametersthat describe the sensor's sensing characteristics, like itssensitivity, are established for use in the calibration adjustment.However in vitro testing of the sensor can destroy, degrade,contaminate, or otherwise render the sensor not suitable fordistribution from the possession of the manufacturer to the possessionof users (e.g., for clinical testing, commercial use, etc.), and thus invitro testing each sensor prior to distribution is not a practicaloption.

Examples of In Vivo Calibration

After using an in vivo sensor to obtain a raw measurement signal fromthe user's body, the on body electronics can apply analog signalconditioning to the raw signal and convert the signal into a digitalform of the conditioned raw signal. For example, the digital raw datacan be in counts converted by an A/D converter from the raw analogsignal (for example, voltage or amps). In some embodiments, thisconditioned raw digital data can be encoded for transmission to anotherdevice, e.g., a display device as described herein, which thenalgorithmically processes that digital raw data into a processed resultrepresentative of the user's analyte level (e.g., a result readily madesuitable for display to the user). This algorithmic processing utilizesthe calibration information for the sensor to arrive at the processedresult, and can utilize other one or more other variables depending uponthe implementation. Algorithmic processes for using calibrationinformation to convert raw digital data into the processed result arewithin the skill of those in the art. This algorithmically processedresult can then be digitally formatted or graphically processed fordigital display to the user. In other embodiments, the on bodyelectronics itself can algorithmically process the digital raw data intothe processed result that is representative of the user's measuredanalyte level, and then encode and wirelessly communicate that data to adisplay device, which in turn can format or graphically process thereceived data for digital display to the user. In some such embodiments,the on body electronics can further graphically process the processedresult of the data such that it is ready for display, and then displaythat data on a display of on body electronics or transmit the data to adisplay device. In some embodiments, the processed analyte data result(prior to graphic processing) is used by the system (e.g., incorporatedinto a diabetes monitoring regime) without processing for display to theuser. In some embodiments, the on body electronics and/or the displaydevice transmit the digital raw data to another computer system foralgorithmic processing and display.

Certain embodiments of in vivo analyte monitoring systems requirecalibration to occur after implantation of the sensor into the user orpatient, either by user interaction or by the system itself in anautomated fashion. For example, when user interaction is required, theuser performs an in vitro measurement (e.g., a blood glucose (BG)measurement using a finger stick and an in vitro test strip) and entersthis into the system, while the analyte sensor is implanted. The systemthen compares the in vitro measurement with the in vivo signal and,using the differential, determines an estimate of the sensor's in vivosensitivity. The in vivo sensitivity can then be used in an algorithmicprocess to transform the data collected with the sensor to a value thatindicates the user's analyte level. This and other processes thatrequire user action to perform calibration are referred to as “usercalibration.” Systems may require user calibration due to instability ofthe sensor's sensitivity, such that the sensitivity drifts or changesover time. Thus, multiple user calibrations (e.g., according to aperiodic (e.g., daily) schedule or on an as-needed basis) may berequired to maintain accuracy. While the embodiments described hereincan incorporate a degree of user calibration for a particularimplementation, generally this is not preferred as it requires the userto perform a painful or otherwise burdensome BG measurement, and canintroduce user error.

Some embodiments of in vivo analyte monitoring systems have beenproposed that regularly adjust the calibration parameters through theuse of automated measurements of characteristics of the sensor made bythe system itself (e.g., processing circuitry executing software). Onesuch system repeatedly measures the sensor's impedance and uses this toupdate the sensitivity, and is described in US Publ. No. 2012/0265037,which is incorporated by reference herein in its entirety for allpurposes. The repeated adjustment of the sensor's sensitivity based on avariable measured by the system (and not the user) is referred togenerally as “system” (or automated) calibration, and can be performedwith user calibration, such as an early BG measurement, or without usercalibration. Like the case with repeated user calibrations, repeatedsystem calibrations are typically necessitated by drift in the sensor'ssensitivity over time. Thus, while the embodiments described herein canbe used with a degree of automated system calibration, preferably thesensor's sensitivity is relatively stable over time such thatpost-implantation calibration is not required.

Some embodiments of in vivo analyte monitoring systems operate with asensor that is factory calibrated. Factory calibration refers to thedetermination or estimation of the one or more calibration parametersprior to distribution to the user or healthcare professional (HCP). Thecalibration parameter can be determined by the sensor manufacturer (orthe manufacturer of the other components of the sensor control device ifthe two entities are different). Many in vivo sensor manufacturingprocesses fabricate the sensors in groups or batches referred to asproduction lots, manufacturing stage lots, or simply lots. A single lotcan include thousands of sensors.

Production lots are often individually numbered or coded to providetraceability throughout the manufacturing process. In some examples offactory calibration, one or a subset of sensors from each individual lotis tested and one or more nominal calibration parameters are determinedand applied to the remaining, untested sensors in that particular lotthat are designated for distribution into the field (e.g., forcommercial use, clinical testing, etc.). Thus, each and every sensordistributed from that lot is assigned the same nominal calibrationparameter. This can be referred to as “lot-level” calibration and,depending on the outcome of the lot testing, the sensors of a first lotmay have a calibration parameter that is different than the sensors of asecond lot.

One or more calibration parameters can be stored in the memory of thecorresponding sensor control devices, such that when a user initiatesoperation of the sensor control device, the requisite calibrationparameters are readily available. Embodiments of factory calibratedsensors with relatively unstable sensitivities can be used with one ormore user calibration steps and/or one or more system calibration steps.

Factory calibrated sensors with stable or substantially stablesensitivities can be operated without user calibration and withoutsystem calibration. For example, in all of the embodiments describedherein, the in vivo sensors can be calibrated by the manufacturer andthen provided to the user, who can then use such sensors for theduration of their lifespan to accurately monitor the user's in vivoanalyte levels, and no step of user calibration nor step of systemcalibration is performed during that lifespan. Such systems and methodsdetermine clinically accurate analyte concentrations at least over thepredetermined sensing period of analyte sensor systems without obtainingone or more independent analyte measurements (e.g., without using an invitro test strip or other reference device) for calibration of agenerated analyte related signal from the analyte sensor during theusage life of the sensor, e.g., post-manufacture. In other words, oncethe analyte sensors are positioned in the body of the user, controllogic or microprocessors in the electronics, or the microprocessors inthe display device include one or more algorithms or programming toaccurately convert or correlate signals related to the sensed analyte(e.g., in nanoamps (nA), counts, or other appropriate units) to acorresponding analyte level (e.g., converted to an analyte level inmilligrams per deciliter (mg/dL) or other appropriate units) without areference value provided to the system, rendering sensor calibration“invisible” to the user such that the system does not require any humanintervention for analyte sensor calibration.

Examples of In Vitro Calibration

Like in vivo analyte monitoring systems, in vitro analyte monitoringsystems can also benefit from calibration. In vitro strips are typicallyused only once, and any calibration information associated with that invitro sensor is determined by the manufacturer and not by the user. Insome examples, the calibration parameter or code can be printed on thepackaging containing the group of in vitro sensors. Each time the useruses one of the in vitro sensors, the user enters the calibrationparameter into the meter so that the meter can appropriately adjust theresult. The algorithmic processing performed by the in vitro systems issimilar to that described with respect to the in vivo systems, where araw measurement signal can undergo analog conditioning and conversioninto a digital form of the conditioned raw signal, and thenalgorithmically processed into a processed result representative of theuser's analyte level (e.g., a result readily made suitable for displayto the user). This algorithmic processing utilizes the calibrationinformation for the in vitro sensor to arrive at the processed result,and can utilize other one or more other variables depending upon theimplementation. As with factory-calibrated in vivo sensors, thecalibration code is determined for a production lot of in vitro sensors(or multiple production lots) and each in vitro sensor within theproduction lot is assigned the same calibration code.

Example Embodiments Relating to Individualized Calibration For MedicalDevices

Many medical device manufacturing processes fabricate the medicaldevices in production lots. In vivo analyte sensors and in vitro analytesensors (e.g., test strips) are just a few examples of medical devicesmanufacturable by lot. The example embodiments described herein allow anindividualized calibration parameter to be independently determined, orestimated, for each and every medical device within a lot. Thus, insteadof lot-level calibration, the embodiments allow for individual“device-level” calibration (e.g., “sensor-level” calibration). The terms“individualized calibration information” and “individualized calibrationparameter” as used herein represent calibration information or acalibration parameter that has been determined using (or is otherwisebased on or represents) at least one characteristic, measurement, oraspect that is specific to an individual medical device within a group(e.g., a production lot) and that can vary across the medical devices ofthe group. While “individualized calibration information” and an“individualized calibration parameter” may also be determined using acharacteristic, measurement, or aspect that is not specific to anindividual medical device but rather shared by the medical deviceswithin the group, those terms remain distinguishable from both lot-levelcalibration information and a lot-level calibration parameter. Theindividualized calibration parameter can be determined for a particularmedical device without in vitro testing that particular medical device,as that testing can render the device unsuitable for distribution tothird party users as described above.

FIG. 20A is a flow diagram depicting an example embodiment of a method2000 for individually calibrating a medical device capable of sensing abiomedical attribute. At 2008, a sensing characteristic of a firstmedical device is determined. For an analyte sensor, this sensingcharacteristic can be a sensitivity to the analyte for example. Thesensing characteristic can be determined with in vitro (or in vivo)testing, such that the testing renders the first medical deviceunsuitable for distribution. At 2009, calibration information for asecond medical device can be determined using at least a representationof a manufacturing parameter of the second medical device and arepresentation of the sensing characteristic of the first medicaldevice. The representation of the manufacturing parameter can be thevalue of the manufacturing parameter as measured, a representative valuethat is calculated from the manufacturing parameter (e.g., a relativedifference of the manufacturing parameter from a reference (nominalvalue or central tendency of the manufacturing parameter)), arepresentative aspect of the manufacturing parameter, or otherwise. Therepresentation of the sensing characteristic, as will be describedfurther below, can be the value of the sensing characteristic itself, arepresentative value that is calculated from the sensing characteristic(e.g., a relative difference of the sensing characteristic from areference (nominal value or central tendency of the sensingcharacteristic)), a representative aspect of the sensing characteristic,or otherwise. The first and second medical devices are preferably of thesame structural and chemical configuration and design.

In many cases the manufacturing parameter is specific to the secondmedical device. For example, the second device's manufacturing parametercan be measured directly or indirectly from the second device during orafter manufacturing. Examples of manufacturing parameters are describedin greater detail herein. The manufacturing parameter of the seconddevice can be used with the sensing characteristic of the first deviceto determine, estimate, calculate, or extrapolate calibrationinformation for the second device. In this manner, calibrationinformation specific to the second device can be determined usingcharacteristics of the second device that are obtained in anon-degrading, non-destructive or non-contaminatory manner, while alsoutilizing an actual sensing characteristic measured from the firstmedical device.

The method of FIG. 20A was described with respect to two individualmedical devices (a first and a second), but this subject matter can beextended to larger scales. FIG. 20B is a flow diagram depicting anotherexample embodiment of a method 2010 for individually calibrating amultitude of medical devices (e.g., in vivo or in vitro analyte sensors)capable sensing a biochemical attribute. At 2018, a sensingcharacteristic of a first subset of medical devices is determined. Thisfirst subset can be referred to herein as a sample subset, or a baselinesubset, and the sensing characteristic taken from the first subset canbe referred to herein as a sample sensing characteristic or baselinesensing characteristic. For analyte sensors, this sensing characteristiccan be a sensitivity to the analyte for example. The sensingcharacteristic can be determined with in vitro (or in vivo ifapplicable) testing of the first subset of medical devices, such thatthe testing renders the first subset of medical devices unsuitable fordistribution. Examples of testing will be described in more detailherein.

At 2019, calibration information can be independently determined foreach medical device within a second subset of medical devices using atleast a representation of an individualized manufacturing parameter ofeach device within the second subset and a representation of the sensingcharacteristic of the first subset of medical devices. Put differently,for example, if the second subset includes 100 individual medicaldevices, then 100 independent determinations of calibration informationcan be made (e.g., by processing circuitry executing softwareinstructions). These 100 independent determinations can be performed as100 discrete mathematical steps, or in one mathematical step such as byusing number arrays. The second subset of medical devices corresponds tothe subset intended for distribution to users such as patients and/orHCPs, and can be referred to herein as the distribution subset.

The medical devices within the baseline subset that are subject to invitro testing are different from the medical devices within thedistribution subset. In some embodiments, the baseline and distributionsubsets are portions of a larger multitude of medical devices that haveundergone one or more manufacturing steps together as a common group orbatch. For example, the larger multitude can be a production lot thatundergoes all or almost all manufacturing steps together. The baselinesubset of medical devices can be taken from the production lot and usedto derive the baseline sensing characteristic that is then used in partto determine the individualized calibration information for each sensorwithin the distribution subset. The baseline subset and distributionsubset together do not have to account for every medical device withinthe production lot as certain medical devices within the lot can beremoved (e.g., for failing an in-line inspection) or utilized for otherpurposes (e.g., quality control).

It is desirable to take the baseline subset and distribution subset fromthe same lot as this will inherently account for many manufacturingvariations, particularly those that occur uniformly across the lot butmay vary between lots. However, for manufacturing processes wheresignificant variations are more limited within and between lots, thenthe medical devices within the baseline subset and the distributionsubset are not taken from the same lot, although care should be taken soas not to significantly lessen the applicability of the baseline testresults to the distribution subset. For example, in some embodiments,the medical devices within the baseline subset can be taken from two ormore different production lots and the distribution subset can be takenfrom a production lot that is the same as the production lot of one ormore medical devices within the baseline subset (e.g., the baselinesubset represents a cross-section of many production lots to which thebaseline sensing characteristic is then applied). In other embodiments,the baseline subset of medical devices can be taken from one productionlot and the distribution subset of medical devices can be taken from asecond, different production lot. In still other embodiments, thebaseline subset can be taken from two or more different production lotsand the distribution subset can be taken from a production lot fromwhich no sensor is included within the baseline subset. In theembodiments just described, the notion of whether baseline anddistribution subsets come from the same or different production lots isviewed with respect to whether the devices were processed togetherduring one or more manufacturing stages.

Generally, the more medical devices within the baseline subset, the moreaccurate the resulting in vitro sensing characteristic will be. However,because the in vitro testing is often destructive etc., the medicaldevices within the baseline subset will generally not be available fordistribution. Thus, the quantity of devices in the baseline subset canbe determined by balancing the ability to obtain accurate andrepresentative results against the decrease to production yields (andcost resulting therefrom). The quantity of devices in the baselinesubset can also be related to the quantity of devices within theproduction lot (or an average production lot). For example only, thebaseline subset can be approximately 0.01-10% (e.g., 0.01%, 0.1%, 0.5%,1.0%, 5%, or 10%) of the medical devices within a production lot. By wayof another example, the number of medical devices within the baselinesubset can be approximately 0.01-10% (e.g., 0.01%, 0.1%, 1.0%, 5%, or10%) of the number of medical devices within the distribution subset.Percentages outside of these ranges are also within the scope of thisdisclosure.

FIG. 20C is a flow diagram depicting another example embodiment ofmethod 2010 (FIG. 20B) with additional steps that can be included bydiscretion. At 2012, a multitude (e.g., a production lot or portionthereof) of medical devices are at least partially manufactured, wherethe multitude includes a baseline subset and a distribution subset. At2014, an individualized manufacturing parameter of each medical devicein the multitude is measured. In some embodiments, the individualizedmanufacturing parameter is only measured for those medical devices inthe distribution subset. The measuring step can be performed while themultitude of medical devices are being manufactured in step 2012, suchas with in-line testing or monitoring occurring during or after eachstage of manufacturing. The measurements can be performed aftermanufacturing of the medical device is complete, such as for thosemanufacturing parameters that are measurable at that stage. If themedical device is subsequently assembled with other components into alarger device, then measurements can be made after that assembly, ifthose manufacturing parameters remain measurable. At 2016, the medicaldevices within the baseline subset are in vitro tested to obtain invitro test data. In vitro testing can be performed after manufacturingof the sensors has reached a stage that permits accurate in vitrotesting (e.g., after application and postprocessing of the membrane butprior to assembly of the sensor with the electrical componentsassociated therewith). As with the embodiment if FIG. 20B, at 2018, asensing characteristic of the baseline subset of medical devices isdetermined and then at 2019, calibration information can beindependently determined for each medical device within the distributionsubset using at least a representation of an individualizedmanufacturing parameter of each medical device within the distributionsubset and a representation of the sensing characteristic of thebaseline subset of medical devices.

At 2020, the calibration information can be associated with eachindividual medical device. Various techniques for doing this aredescribed in greater detail herein. For example, for in vivo devices,this can be achieved by storing the individualized calibrationinformation within non-transitory memory of electronics assigned to theindividual in vivo device, or by storing the individualized calibrationinformation in non-transitory memory associated with a server such thatthe calibration information can be communicated to a device in the field(e.g., a reader device) that is operating with the individual in vivosensor. For in vitro devices, this can be accomplished by recording thecalibration information on a medium located on or with each individualin vitro device. In certain examples where the in vitro devices arestrips, the strips can be packaged together with other strips having thesame individually determined calibration information, which can beprinted on the packaging.

Examples of Manufacturing Parameters

The term manufacturing parameter is a broad one intended to encompassany aspect of a medical device measurable (directly or indirectly)during or after the manufacturing process, or any descriptor of themanner in which a particular medical device (or group of medicaldevices) was manufactured. The manufacturing parameter is preferablyspecific to one individual medical device such that it can vary betweenmedical devices in the same group or lot, in which case it is referredto herein as an individualized manufacturing parameter. This is incontrast to a manufacturing parameter that is not specific to oneindividual medical device, which is referred to herein as a “group”manufacturing parameter or “lot” manufacturing parameter. Examples ofwhich can include an environmental parameter present while a batch ofmedical devices are concurrently processed (such as in a commonchamber), or an identification of equipment that is used to manufacturea production lot.

The medical devices are preferably traceable throughout themanufacturing process such that the identity of the medical deviceduring each manufacturing stage can be tracked. An individualizedmanufacturing parameter can be stored as data in a manner thatassociates it with the respective individual medical device from whichit was obtained. When a manufacturing parameter is obtained for aparticular medical device, that newly obtained manufacturing parametercan be stored with any and all other manufacturing parameters measuredfor that same medical device. Each individual medical device cantherefore have one or more manufacturing parameters associated with it,for example, in a data or log file.

Examples of manufacturing parameters can include size or dimensionalmeasurements of an individual medical device. The dimensionalmeasurement can be any dimension in three-dimensional space. The sizemeasurement can be one-dimensional, such as a length, width, height,thickness, radius, diameter, chord, or otherwise. The size measurementcan represent a two-dimensional (2D) space, such as an area of a planarsurface or a magnitude of a periphery of a planar surface, an arc, orotherwise. The size measurement can represent a three-dimensional (3D)space, such as an area of a nonplanar surface (e.g., cylindrical,hemispherical, irregular or portions thereof), a volume, or otherwise.Dimensional measurements can be obtainable directly or indirectly. Forexample, 2D and 3D measurements can be obtained by measuring varioussingle dimensions and then calculating or estimating the 2D or 3D size.In some examples, dimensions such as height or thickness of a particularstructure may be difficult to measure directly, but can be estimated bymeasuring other comparable structures (e.g., artwork) that can act as asurrogate. Size measurements can be obtained using inspection equipment(e.g., optical sensors) or the like.

In the context of in vivo analyte sensors, all the aforementioned sizescan be measured from any component thereof, such as any and allelectrodes, a sensing region, a membrane, a contact, an insulatingmember, a substrate, an electrical trace, and so forth. In manyembodiments, as will be described herein, the size or dimensionalcharacteristics of the sensing region and/or the membrane of an in vivoanalyte sensor can be particularly important in determining accuratecalibration information for the sensor, although the embodimentsdescribed herein are not limited to only these examples. By way ofnon-limiting example, the size of the sensing region can berepresentative of at least one of the following: a width of the sensingregion, a length of the sensing region, a thickness of the sensingregion, a peripheral length of the sensing region, an area of thesensing region, or a volume of the sensing region. By way ofnon-limiting example, the size of the membrane can be representative ofat least one of the following: a width of the membrane, a length of themembrane, a thickness of the membrane, a peripheral length of themembrane, an area of the membrane, or a volume of the membrane.

In the context of in vitro analyte sensors such as strips, all theaforementioned sizes can be measured from any component thereof, such asany and all electrodes, a working pad, a working ink, an insulatingmember, a substrate, a spacer, a trace, a cutout, and so forth. In someembodiments, the size (e.g., length, width, area, thickness or height,perimeter, volume, etc.) of the working pad can be particularlyimportant in determining accurate calibration information, although theembodiments described herein are not limited to such.

Examples of manufacturing parameters can include chemical compositionsor concentrations of any portion or component of the medical device. Thechemical composition or concentration can be that of any of thestructures described herein or otherwise known in the art. In thecontext of in vivo analyte sensors, the chemical composition can be thatof any and all electrodes, a sensing region and components thereof, amembrane, a contact, a substrate, an insulating layer, an electricaltrace, and so forth. In the context of in vitro sensors such as strips,the chemical composition can be that of any and all electrodes, aworking pad, a working ink, an insulating member, a substrate, a spacer,an electrical trace, and so forth. Numerous chemical aspects of medicaldevices are described herein and these will not be repeated other thanto note that the manufacturing parameter can relate to the compositionand/or concentration of each chemical aspect described. In addition, thechemical composition or concentration can be representative of animpurity level within the medical device. Examples of manufacturingparameters can also include material characteristics, such as porosity,surface roughness or smoothness, density, frangibility, conduit width,conduit length, and the like.

Examples of manufacturing parameters can include electricalcharacteristics such as resistance, impedance, capacitance, leakage, andso forth. In the context of in vivo analyte sensors, the electricalcharacteristics can be measured from any component thereof, such as anyand all electrodes, conductive members (such as wires, interconnects,traces, or contacts), insulating members (e.g., resistance, impedance,leakage), the sensing region, the membrane, a substrate, and so forth.In the context of in vitro sensors such as strips, the electricalcharacteristics can be measured from any component thereof, such as anyand all electrodes, conductive members (such as wires, interconnects,traces, or contacts), insulating members, substrates, the working pad,the working ink, a spacer, and so forth. In some embodiments, the traceresistances can be particularly important in determining accuratecalibration information, although the embodiments described herein arenot limited to such.

Examples of manufacturing parameters that can be either individualizedparameters (e.g., such as with single unit processing where anindividual medical device is acted upon alone by the manufacturingequipment of a particular stage) or that are not individualized (e.g.,such as with batch processing), can include environmental conditions.One example can be temperatures or amounts of temperature variationexhibited during a particular manufacturing stage, such as an anneal.Another example can be ambient pressures or amounts of pressurevariation exhibited during a particular manufacturing stage, such as avapor deposition. The amount of time a particular medical device (orbatch or production lot) spends in a particular stage of manufacturing,or between stages of manufacturing if such is relevant, can also qualifyas a manufacturing parameter

Manufacturing parameters can be qualitative as well. The identity of aparticular piece of equipment used on the medical device duringmanufacturing can be a qualitative manufacturing parameter, as can theorder in which medical devices are processed. For example, the positionof a particular medical device (or batch of medical devices) within asequence of medical devices (or batches of medical devices) being actedupon by a particular piece of equipment can be a qualitativemanufacturing parameter. In some embodiments, in vitro strips can befabricated from a printed card that is subsequently separated intoindividual test strips, and the position of the strip in each row can beparticularly important in determining accurate calibration information,although the embodiments described herein are not limited to such.Likewise, the fact that a medical device is subjected to reprocessing atany stage during manufacturing, e.g., for being out of specification,can be a qualitative manufacturing parameter.

Referring back to measurements of a sensing region area of an examplesensor, FIG. 21A is a top down view depicting an example embodiment ofthe surface of a substrate 2102 having a sensing region that includesthree sensing elements 2103-1, 2103-2, and 2103-3 with diametersindicated, and the area of the sensing region can be the sum of the areaof each of the three sensing elements. FIGS. 21B-C are cross-sectionalviews taken along line 21BC-21BC, where electrodes and other componentsare omitted for simplicity. In FIG. 21B, each of the three sensingelements 2103 has a planar surface. In FIG. 21C, each of the threesensing elements 2103 as a domed or rounded surface the area of whichcan be approximated as the area of a two-dimensional circle orcalculated as a three-dimensional structure. FIG. 22A is a top down viewdepicting an example embodiment of the surface of a substrate 2202having a sensing region that includes one sensing layer 2203, the areaof which can be determined as the product of the length 2204 and width2205. FIGS. 22B-C are cross-sectional views taken along line 22BC-22BC,where electrodes and other components are omitted for simplicity. InFIG. 22B, sensing layer 2203 is disposed above substrate 2202 while inFIG. 22C, sensing layer 2203 is inset or disposed within a well createdwithin substrate 2202. FIG. 23A is a perspective view depicting anexample embodiment of a section of a cylindrical or substantiallycylindrical in vivo sensor 2301 having a sensing region 2303 locatedbetween insulative (or non-sensing) portions 2302. FIG. 23B is across-sectional view taken along line 23B-23B of FIG. 23A and depictssensing region 2303 surrounding a core region 2305, which can beconductive material. In this embodiment the area of sensing region 2303can be calculated as the area of a cylinder with a length 2304 anddiameter 2306.

Referring back to measurements of membrane thickness, FIG. 24 is across-sectional view depicting an example embodiment of an in vivosensor 2401 having a substrate 2402, a sensing region 2403, and amembrane 2404 that encompasses the terminal end of substrate 2402 andsensing region 2403. The thickness of membrane 2404 can be determined bytaking one or more measurements 2406 between the outer surface 2407 ofmembrane 2404 and surface 2408 of substrate 2402. Examples of variousmeasurement locations are depicted by arrows 2406-1 through 2406-4,which can be aligned or coincide with sensing region 2403 (locations2406-2 and 2406-3) or outside of sensing region 2403 (locations 2406-1and 2406-4). If multiple measurements of membrane thickness are taken,then the value used as the individualized manufacturing parameter can bea central tendency (e.g., median, mean) of those measurements. In somecases it may be difficult to measure membrane thickness directly, inwhich case it can be inferred by measuring the total thickness ordiameter 2409 of the membrane 2404 between surfaces 2407 and 2410 (ifmeasured multiple times in a central tendency can be taken) and a known,nominal, or estimated thickness 2411 of substrate 2402 (or substrate2402 and sensing region 2403) can be subtracted from the total thickness2409, and then halved) or otherwise divided as appropriate) to estimatethe thickness of membrane 2404 in the region between surfaces 2407 and2408 (or between surface 2407 and the upper surface of sensing region2403). FIG. 25A is a perspective view of an example embodiment of asensor 2501 similar to that of FIG. 23A but showing an outer membrane2504. FIG. 25B is a cross-sectional view taken along line 25B-25B ofFIG. 25A that shows core region 2305 with sensing region 2303 locatedthereon and membrane 2504 located on sensing region 2503. A thickness ofmembrane 2504 as indicated by 2506.

Examples of Sensing Characteristics Derived from Testing

As described, one or more medical devices within the baseline subset canbe tested to empirically determine a sensing characteristic for thatbaseline subset. The testing is, in many embodiments, capable ofproducing data that verifiably represents the ability of the medicaldevice to sense the biochemical attribute. In many in vivo analytesensor and in vitro analyte sensor (e.g., test strip) embodiments, thesensing characteristic can be the sensitivity of the analyte sensor tothe presence of the analyte. Often this testing will be performed invitro and will result in the collection of in vitro test data. Thesensing characteristic derived or otherwise resulting from the in vitrotest data for the baseline subset can be referred to as an in vitrosensing characteristic (e.g., in vitro sensitivity).

FIG. 26A is an example plot of in vitro test data obtained by in vitrotesting amperometric in vivo glucose sensors constituting a baselinesubset. In this example, the baseline subset includes five sensors andthe in vitro test data sets corresponding to each of those five sensorsare labeled 2602-1 through 2602-5. The baseline subset may includequantities other than five, without departing from the scope of thepresent subject matter. The in vitro test data sets were obtained byapplying various glucose solutions to each analyte sensor and monitoringthe electrical current produced as a result, which can be on the orderof nanoamps, picoamps, or otherwise depending on the sensor design. Fromtime t0 to time t1 no solution is applied to the sensors (or a solutionhaving no glucose concentration is applied). At time t1 a first glucosesolution having a first relatively low concentration (e.g., onemillimole per liter (mmol/L)) is applied to the in vivo sensor and theresulting response is recorded. At time t2 a second glucose solutionhaving a relatively higher concentration than the first solution isapplied to the in vivo sensor and the resulting response is againrecorded. The process can proceed iteratively at t3 and thereafter withever increasing concentrations of glucose solution to obtain empiricaldata representing the sensitivity of the in vivo glucose sensor across awide range of glucose concentrations. As can be seen, these embodimentsof the glucose sensors react differently to the presence of the glucosesolution and these differences become more pronounced as theconcentration of the glucose solution increases. Note that the x-axisindicates time and not glucose concentration, so while the in vitro testdata may appear to be slightly nonlinear, the resulting sensitivityderived from the in vitro test data can still be linear.

FIG. 26B is an example plot of sensitivities 2604-1 through 2604-5corresponding to the in vitro test data sets 2602-1 through 2602-5 ofFIG. 26A. Sensitivities 2604-1 through 2604-5 can be determined byperforming a regression (e.g., linear or non-linear) independently oneach respective in vitro test data set 2602-1 through 2602-5. In someembodiments, such as for nonlinear sensitivities, the in vitro data setcan be portioned to separate response zones, with each zone beingmodeled with a linear sensitivity to approximate the nonlinear curve,such that the resulting calibration information will differ depending onthe degree of response (e.g., current) being measured.

In the example of FIG. 26B, the various sensitivities 2604 are eachlinear or substantially linear. The in vitro sensitivity (or othersensing characteristic) of the baseline subset can be determined in anydesired fashion. In some embodiments, the baseline in vitro sensitivitycan be a central tendency of sensitivities 2604-1 through 2604-5, suchas a mean or median of sensitivities 2604-1 through 2604-5. The medianin this example would be sensitivity 2604-3. In some embodiments, thebaseline in vitro sensitivity can be a central tendency (e.g., mean ormedian) of one aspect or characteristic of sensitivities 2604-1 through2604-5, such as the central tendency of the slopes of sensitivities2604-1 through 2604-5 or the central tendency of the intercepts ofsensitivities 2604-1 through 2604-5. Other aspects of the sensitivitiescan also be used as the in vitro sensitivity for the baseline subset. Insome embodiments, instead of deriving individual sensitivities 2604-1through 2604-5 from each of the in vitro test data sets 2602-1 through2602-5, a single regression can be performed for the entirety of the invitro test data from the baseline subset and this single regression, oran aspect thereof, can be used as the baseline in vitro sensitivity. Inall of these embodiments, the in vitro test data sets or the in vitrosensing characteristics determined therefrom (such as those shown inFIG. 26B) can be filtered to remove one or more values (e.g., valuesbelow a minimum threshold, above a maximum threshold, within athreshold, atypical values, etc.) prior to determining the baseline invitro sensitivity.

Additional Example Embodiments Relating to Individualized FactoryCalibration

Turning back to example embodiments for individualized calibration,FIGS. 27A, 27B, and 27C are flow diagrams depicting example embodimentsof methods 2700, 2710, and 2720, respectively, of determiningindividualized calibration information, such as could be performed instep 2009 of the embodiment of FIG. 20A, or step 2019 of the embodimentsof FIGS. 20B and 20C. In many embodiments, methods 2700, 2710, and 2720are performed independently for each medical device in the distributionsubset. The methods refer to a “respective” medical device, which, inthis and the other embodiments described herein, is one particularmedical device in the subset (e.g., distribution or baseline) thatchanges each time the method is performed. Here, the “respective”medical device is a first medical device of the distribution subset thefirst time method 2700 is performed, the respective medical device thenbecomes the second medical device the second time method 2700 isperformed, and so forth until method 2700 has been performedindependently on all medical devices in the distribution subset. Thesame applies to methods 2710 and 2720. Methods 2700, 2710, and 2720 aredescribed with respect to a representation of an individualizedmanufacturing parameter but can also be applied with anon-individualized (e.g., environmental) manufacturing parameter.Likewise, methods 2700, 2710, and 2720 are described with respect to arepresentation of an in vitro sensing characteristic but can also beapplied with other sensing characteristics (or representations thereof).

Turning now to FIG. 27A, at 2702, an in vitro sensing characteristic (ora representation thereof) of a respective medical device in thedistribution subset is determined using at least a representation of theindividualized manufacturing parameter for the respective medical deviceand a representation of the in vitro sensing characteristic of thebaseline subset. At 2705, individualized calibration information isdetermined for the respective medical device that corresponds to therepresentation of the in vitro sensing characteristic of the respectivemedical device. This individualized calibration information can bedetermined directly from the in vitro sensing characteristic of 2702, orthe in vitro sensing characteristic can be modified or converted toanother value, in one or more steps, and the resulting modified orconverted value can then be used to determine the individualizedcalibration information.

FIG. 27B depicts method 2710, which can have particular applicability toan in vivo medical device. Here, at 2712 an in vitro sensingcharacteristic (or a representation thereof) of a respective medicaldevice in the distribution subset is determined using at least arepresentation of the individualized manufacturing parameter for therespective medical device and a representation of the in vitro sensingcharacteristic of the baseline subset. This can be performed by applyinga model to at least the representation of the individualizedmanufacturing parameter and the representation of the baseline in vitrosensing characteristic into a model or equation, such that the in vitrosensing characteristic for the respective medical device (or arepresentation thereof) is produced by the model. At 2714, arepresentation of an in vivo sensing characteristic of the respectivemedical device can be determined using at least a representation of thein vitro sensing characteristic of the respective medical device. At2715, individualized calibration information is determined for therespective medical device that corresponds to the representation of thein vivo sensing characteristic of the respective medical device.

FIG. 27C depicts method 2720, which can have particular applicability toan in vitro medical device where the in vitro sensing characteristic ismodified prior to determining individualized calibration information.Here, at 2722 a first in vitro sensing characteristic (or arepresentation thereof) of a respective medical device in thedistribution subset is determined using at least a representation of theindividualized manufacturing parameter for the respective medical deviceand a representation of the in vitro sensing characteristic of thebaseline subset. As with the prior example, this can be performed byinputting at least the representation of the individualizedmanufacturing parameter and the representation of the baseline in vitrosensing characteristic into a model or equation that outputs the firstin vitro sensing characteristic for the respective medical device (or arepresentation thereof). At 2724, a second in vitro sensingcharacteristic (or a representation thereof) of the respective medicaldevice can be determined using at least a representation of the first invitro sensing characteristic of the respective medical device. At 2725,individualized calibration information is determined for the respectivemedical device that corresponds to the representation of the second invitro sensing characteristic of the respective medical device. Anexample application for method 2720 is with an in vitro test strip,where the first in vitro sensing characteristic corresponds to testresults obtained by in vitro testing with a glucose solution, which canthen be modified (such as with a transfer function described in moredetail herein) to the second in vitro sensing characteristic, whichcorresponds to the sensing characteristic in the presence of the sampledbodily fluid (e.g., blood).

For embodiments where the manufacturing parameter is a quantitativevalue or measurement, the representation of the manufacturing parameter(or individualized manufacturing parameter) can be an actual measuredvalue of the manufacturing parameter, a relative indication of themeasured manufacturing parameter, or other information calculated orderived from the actual measured value. In certain example embodiments,it may be desirable to use the relative difference of a quantitativelymeasured manufacturing parameter from a central tendency (e.g., mean,median, etc.) of the quantitatively measured manufacturing parameter fora larger group (e.g., the entire lot or the entire distribution subset,etc.). The manufacturing parameter can be an area of a sensing region ofthe medical device for example. Instead of using the actual measurementof the area of the sensing region (or the measured length and width ofthe sensing region) to determine the calibration information, it may bedesirable to use the relative difference of the measured sensing areafrom a central tendency of the sensing area for the larger group. For aquantitative manufacturing parameter (MP) that varies between individualmedical devices, a relative representation of that manufacturingparameter (RMP) can be determined according to (1) immediately below:

${RMP} = {100*\left( \frac{\left( {{{MP}{of}{Individual}{Medical}{Device}} - \text{ }{{Central}{Tendency}{of}{MP}{of}{Group}}} \right)}{{Central}{Tendency}{of}{MP}{of}{Group}} \right)}$

As already noted, other manufacturing parameters for various devices,such as membrane thickness, working pad area, working ink resistance,etc., can be used with or instead of the sensing area. Similarly, therepresentation of the baseline in vitro sensing characteristic can bethe actual in vitro sensing characteristic determined for the baselinesubset, a relative indication of the degree of variation of that invitro sensing characteristic from another sensing characteristic (e.g.,such as a benchmark), or otherwise. Likewise, the representation of thein vivo sensing characteristic can be an estimated in vivo sensingcharacteristic, a relative indication of the degree of variation of thein vivo sensing characteristic from another sensing characteristic(e.g., a benchmark), or otherwise.

Steps 2702, 2712, and 2722 of methods 2700, 2710, and 2720,respectively, can be performed by inputting at least the representationof the individualized manufacturing parameter and the representation ofthe baseline in vitro sensing characteristic into a model (or equation)that outputs a representation of the in vitro sensing characteristic forthe individual medical device. Many different models (or equations) canbe used, including but not limited to a linear regression model; amultiple variable regression model, a random forest model, a non-linearmodel, a Bayesian regression model, a neural network, a machine learningmodel, a non-random decision tree, or a discriminant analysis model, toname a few. Examples of models incorporating or determined by multiplevariable regression analysis are described below, while examples ofthese other models are further discussed in the appendix section.

Many example embodiments described herein determine the sensingcharacteristic for the individual medical device by utilizing amanufacturing parameter of that individual medical device centeredaround the empirically determined baseline sensing characteristic. Insome embodiments, the individualized calibration information isdetermined directly from the individualized manufacturing parameterswithout reference to the baseline sensing characteristic. However,incorporation of the empirically determined baseline sensingcharacteristic into a model, particularly when the representation of themanufacturing parameter is a relative difference from the group atlarge, can minimize the effects of group-to-group (e.g., lot-to-lot)variations. The following (2, 3) are examples of a multiple variableregression-based model that can be used with embodiments describedherein:

SC_(MD)=SC_(B)+α+(βRMP_(A))  (2)

SC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A))))  (3)

where SC_(MD) is the modeled or calculated in vitro sensingcharacteristic for the individual medical device, SC_(B) is the in vitrocharacteristic for the baseline subset, α is an optional adjustmentfactor (zero or non-zero), RMP_(A) is the representation of themanufacturing parameter, and β is a coefficient for RMP_(A). β and α canbe constants (positive or negative) that are empirically determined,e.g., by comparison of estimated in vitro sensing characteristics formedical devices with those that are empirically observed for the samemedical devices. In these examples (2, 3) and the other examples ofmodels (4)-(7) below, RMP is a quantitative measurement, as opposed to aqualitative descriptor, like the identity of manufacturing equipment, oran indication of whether a device was reprocessed. In the above, eq. (3)takes the form of a more relative correction than eq. (2). A constantvalue other than 0.1 can be used in eq. (3), and in eqs. (5) and (7)below.

In some embodiments, higher order exponential terms can be includedwithin the model to account for nonlinearities in the manufacturingparameter data. The following (4, 5) are examples of a model with ahigher order term that can be used with all of the embodiments describedherein, where δ can be another empirically determined coefficient forthe RMP_(A) squared term:

SC_(MD)=SC_(B)+α+(βRMP_(A))+(δRMP_(A) ²)  (4)

SC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A))+(δRMP_(A) ²)))  (5)

In some embodiments, the model can make use of multiple differentmanufacturing parameters, with or without higher order terms. Thefollowing (6, 7) are two examples of models utilizing two differentmanufacturing parameters that can be used with all of the embodimentsdescribed herein:

SC_(MD)=SC_(B)+α+(βRMP_(A))+(δRMP_(A))+(γRMP_(B))+(εRMP_(B))+(ρRMP_(A)RMP_(B))  (6)

SC_(MD)=SC_(B)+(1+0.01(α+(βRMP_(A))+(δRMP_(A))+(γRMP_(B))+(εRMP_(B))+(ρRMP_(A)RMP_(B))))  (7)

where RMP_(A) is a first manufacturing parameter, RMP_(B) is a secondmanufacturing parameter, γ is a coefficient for RMP_(B), ε is acoefficient for the RMP_(B) exponential, and ρ is a coefficient for theproduct of RMP_(A) and RMP_(B). Each of these coefficients can also beempirically determined, can be constants, and can be positive ornegative. These coefficients can be determined and then applied acrossall production lots. In other embodiments, these coefficients can bedetermined on a lot-by-lot basis such that the coefficients are constantfor all devices in a lot (or other group) but may differ for all devicesin a different lot (or group). The coefficients can also be determinedon an individual basis. The higher order product of RMP_(A) and RMP_(B)can assist in capturing interactions between those manufacturingparameters. For example, the effect of a relatively lower value ofRMP_(A) (as compared to a nominal value of RMP_(A)) may be greater whenRMP_(B) has a relatively higher value (as compared to a nominal value ofRMP_(B)). Those of ordinary skill in the art can expand and implementthese models with three or more different manufacturing parameters. Anyand all of the coefficients described in (2)-(7) can be weighted, e.g.,to account for a confidence level.

Referring back to FIG. 27B, at 2714 the in vivo sensing characteristicof the respective medical device is determined using the representationof the in vitro sensing characteristic (e.g., in vitro SC_(MD)) of therespective medical device, and referring back to FIG. 27C, at 2724 thesecond in vitro sensing characteristic of the respective medical deviceis determined using the representation of the first in vitro sensingcharacteristic (e.g., in vitro SC_(MD)) of the respective medicaldevice. These and similar determinations described herein can be made byapplying the representation of the in vitro sensing characteristic of2714 (or the first in vitro sensing characteristic of 2724) to atransfer function. Transfer functions for use in converting an in vitrosensing characteristic to an in vivo sensing characteristic, and forconverting between in vitro sensing characteristics are within the skillof those in the art. The transfer function can be determinedanalytically. For example, a transfer function for converting from an invitro sensing characteristic to an in vivo sensing characteristic cantake into account factors that differ between in vitro and in vivostates like absolute glucose concentration, temperature, oxygen, andinterfering substances, to name a few. In addition to these, a transferfunction for converting between in vitro sensing characteristics, suchas one for an analyte test solution and one for a bodily fluid, can alsotake into account hematocrit percentage, for example. The transferfunction can also be determined empirically, for example, by performingclinical studies and comparing the in vivo response to the in vitrodata, or by comparing in vitro responses to different substances. If therelationship is in the form of an offset, then the transfer function canbe accomplished by adding or subtracting a constant value. More complextransfer functions can involve multiplication by a constant value,multiplication by a variable value (e.g., where the variable isdependent on the magnitude of the in vitro sensing characteristic), orothers.

In all of the embodiments herein, a representation of the sensingcharacteristic (e.g., SC_(MD), SC_(B), etc.) can be the sensingcharacteristic itself, (e.g., the sensitivity itself (e.g., a slope andan intercept)), an aspect of the sensing characteristic, such as justthe slope of the sensitivity or just the intercept of the sensitivity, arelative variation of the sensing characteristic from a reference value(e.g., nominal value, mean, average, etc.), a relative variation of theaspect of the sensing characteristic (e.g., relative slope, relativeintercept, etc.) from the reference value (e.g., nominal value, mean,average, etc.), or others. Referring back to methods 2700, 2710, and2720, individualized calibration information is determined from the invitro sensing characteristic of the individual medical device (step 2705of method 2700), from the in vivo sensing characteristic of theindividual medical device (step 2715 of method 2710), or from a secondin vitro sensing characteristic (step 2725 of method 2720). Theindividualized calibration information can capture the sensingcharacteristic in the form of a factor or code that can be recorded orstored in a manner such that it is accessible to the processingcircuitry that processes the raw or conditioned data collected by theindividual medical device. Many different techniques exist for makingcalibration information accessible to the appropriate processingcircuitry and the technique that is implemented is generally dependenton the type of medical device and the needs of the implementation.Several embodiments of devices and techniques for recording and makingindividualized calibration information accessible to the processingcircuitry are described in greater detail below.

FIG. 27D is a flow diagram depicting another example embodiment of amethod 2750 for determining individualized calibration information foran individual medical device. Method 2750 combines many of the aspectsof embodiments discussed previously. At 2752, one or more manufacturingparameters are obtained for N medical devices, where N=X devices of thebaseline subset+Y devices of the distribution subset. In someembodiments, the one or more manufacturing parameters are obtained onlyfor the Y devices of the distribution subset. The manufacturingparameters can be individualized manufacturing parameters ornon-individualized manufacturing parameters (e.g., environmentalfactors, equipment identification, etc.), although if onlynon-individualized manufacturing parameters are measured than theresulting calibration information will also not be individualized. Themanufacturing parameters can be obtained at various different stages ofthe manufacturing process. By way of illustration, in one exampleembodiment where the medical devices are in vivo analyte sensors, atleast two different individualized manufacturing parameters aremeasured: a size of the sensing region after fabrication of the sensingregion, and a size of the membrane after application of the membrane. IfN=1000, then after fabrication of the sensing region for the N sensorsand measurement thereof, 1000 different measurements of sensing regionsizes will have been obtained. After placement (e.g., deposition) of themembrane on the N sensors and measurement thereof, 1000 differentmeasurements of membrane sizes will have been obtained, or 2000measurements in total. Depending upon the quantity and types ofmeasurement equipment, the 1000 different sensing region measurementscan be obtained in serial fashion, in concurrent fashion, or acombination thereof, and the same applies to the measurements ofmembrane size or any other manufacturing parameter.

At 2753, the X devices of the baseline subset are in vitro tested toobtain in vitro test data. The in vitro testing can be performed in amanner similar to that described with respect to FIG. 26A such that thedata is an empirical representation of the in vitro sensingcharacteristic of each of the X devices. Each of the X devices can betested individually to produce an individual in vitro test data set.Where X is greater than one, depending on the number and type of invitro test equipment, the in vitro testing of the X devices can occur inserial fashion, in concurrent fashion, or a combination thereof. If eachof the X devices is individually tested, then performance of step 2753will result in X individual in vitro test data sets. By way ofillustration only, X can be a relatively small fraction of N, such as 5,10, or 20 medical devices when N=1000, with Y being much larger, 995,990, or 980, respectively. Other values of N, X, and Y are within thescope of this disclosure.

At 2754, an in vitro sensing characteristic for the baseline subset isdetermined. In some example embodiments, this can be accomplished byfirst converting the X individual in vitro test data sets into X invitro sensing characteristics (one for each of the X devices), and thendetermining a single in vitro sensing characteristic for the entirebaseline subset (e.g., SC_(B)) from the X in vitro sensingcharacteristics. For example, the baseline in vitro sensingcharacteristic can be a central tendency (e.g., mean or median) of the Xin vitro sensing characteristics. In another embodiment, the baseline invitro sensing characteristic can be determined by performing aregression analysis on the X individual in vitro test data sets. Again,the in vitro sensing characteristic can be the sensitivity or an aspectthereof (e.g., slope or intercept).

At 2755, the individualized calibration information for the Y medicaldevices of the distribution subset is determined. In this embodiment,the individualized calibration information for each particular medicaldevice within the distribution subset is determined in a manner similarto that described with respect to method 2700 of FIG. 27A.

With i=1, at 2756 an estimate of the in vitro sensing characteristic(e.g., SC_(MD)) of the i-th device of the Y devices is determined. Thisestimate can be accomplished, for example, using a model such as thosedescribed herein. Then, at 2758 the individualized calibrationinformation of the i-th medical device is determined from the in vitrosensing characteristic. At 2759, a determination is made whether i=Y. Ifnot, then i is incremented by one (e.g., i=i+1) and method 2750 proceedsback to step 2756. The process repeats itself until i=Y, in which case Yindependent determinations of individualized calibration informationwill have been made, one for each of the Y medical devices.

FIG. 27E is a flow diagram depicting another example embodiment of amethod 2760 for determining individualized calibration information foran individual medical device. Method 2760 combines many of the aspectsof embodiments discussed previously and steps 2752-2756 are similar tothe embodiment of FIG. 27D. At 2755, the individualized calibrationinformation for the Y medical devices of the distribution subset isdetermined. In this embodiment, the individualized calibrationinformation for each particular medical device within the distributionsubset is determined in a manner similar to that described with respectto method 2710 of FIG. 27B and is particularly applicable to in vivodevices.

At 2756, with i=1, an estimate of the in vitro sensing characteristic(e.g., SC_(MD)) of the i-th device of the Y devices is determined.Again, this estimate can be accomplished using a model such as thosedescribed herein. In the example embodiment where the medical devicesare in vivo analyte sensors and the manufacturing parameters are a sizeof the sensing region and a size of the membrane, SCS can be determinedaccording to eqs. (6) or (7), where RMP_(A) is a size (e.g., area) ofthe sensing region and RMP_(B) is a size (e.g., thickness) of themembrane. Then, at 2764 the in vivo sensing characteristic for the i-thmedical device is determined. This can be accomplished, for example, byuse of a transfer function. Then, at 2765 the individualized calibrationinformation of the i-th medical device is determined from the in vivosensing characteristic. At 2759, a determination is made whether i=Y. Ifnot, then i is incremented by one (e.g., i=i+1) and method 2760 proceedsback to step 2756. The process repeats itself until i=Y, in which case Yindependent determinations of individualized calibration informationwill have been made, one for each of the Y medical devices.

FIG. 27F is a flow diagram depicting another example embodiment of amethod 2770 for determining individualized calibration information foran individual medical device. Method 2770 also combines many of theaspects of embodiments discussed previously and steps 2752-2756 aresimilar to the embodiment of FIG. 27D. At 2755, the individualizedcalibration information for the Y medical devices of the distributionsubset is determined. In this embodiment, the individualized calibrationinformation for each particular medical device within the distributionsubset is determined in a manner similar to that described with respectto method 2720 of FIG. 27C and is particularly applicable to in vitrodevices.

At 2756, with i=1, a first estimate of an in vitro sensingcharacteristic (e.g., SC_(MD)) of the i-th device of the Y devices isdetermined. Again, this estimate can be accomplished using a model suchas those described herein. Then, at 2774 a second in vitro sensingcharacteristic for the i-th medical device is determined. This can beaccomplished, for example, by use of a transfer function. Then, at 2775the individualized calibration information of the i-th medical devicecan be determined from the second in vitro sensing characteristic. At2759, a determination is made whether i=Y. If not, then i is incrementedby one (e.g., i=i+1) and method 2760 proceeds back to step 2756. Theprocess repeats itself until i=Y, in which case Y independentdeterminations of individualized calibration information will have beenmade, one for each of the Y medical devices.

In the example embodiments of FIGS. 27D-27F, the substeps within 2755are performed once, in sequence, for one individual medical devicebefore performing those substeps again for the next individual medicaldevice. In other embodiments, each substep can be performed Y timesbefore proceeding to the next substep. For example, with respect to FIG.27F, step 2756 can be performed Y times for all of the Y medical devicesbefore steps 2774 or 2775 are performed. For example, step 2756 can beperformed Y times, then step 2774 can be performed Y times, then step2775 can be performed Y times. In many embodiments, the substeps of 2755(e.g., 2756, 2774, and 2775) will be performed by processing circuitryexecuting software instructions, and those of ordinary skill in the artwill recognize the many different ways these steps can be implemented bythose instructions without departing from the scope of the subjectmatter described herein.

FIGS. 28A and 28B are flow diagrams depicting additional exampleembodiments of methods relating to the determination of individualizedcalibration information. These methods utilize direct analysis ofclinical data to determine or derive a baseline sensing characteristicfor all or a majority of the medical devices produced by themanufacturing process, which in turn minimizes, or eliminatesaltogether, the need for regular in vitro testing of baseline subsetsfrom each production lot (or various lots).

FIG. 28A depicts a method 2800 for determining a baseline sensingcharacteristic from clinical data. At 2802, one or more individualizedmanufacturing parameters are measured (or otherwise obtained) from eachmedical device in a first multitude of medical devices. The resultingmanufacturing parameter data is stored or archived for later use. Then,at 2804, the medical devices from the first multitude are used inclinical testing and the clinical test data resulting there from is alsostored or archived. At 2806, a baseline sensing characteristic can bedetermined from the clinical test data. As with the other embodimentsdescribed herein, the baseline sensing characteristic can be for in vivoor in vitro states of the medical device, and can be, for example, asensitivity or an aspect of the sensitivity of the medical device.

For example, the clinical testing is preferably performed on a sizablepopulation of participants to obtain a robust data set. Traceabilitybetween each participant and the specific medical device or devices usedby that participant is preferably maintained. In this manner, themedical device used by each participant can be tracked and themanufacturing parameters measured from that medical device can becorrelated to the resulting clinical data produced by that medicaldevice and otherwise collected in the clinical test. Then statisticaland/or other analyses can be performed to determine the baseline sensingcharacteristic from that clinical data. In some examples, the baselinesensing characteristic can be a central tendency of the clinical datasuch as a mean or a median. The baseline sensing characteristic ispreferably representative of the medical devices produced by themanufacturing process as a whole. The manner and degree to which themeasured manufacturing parameters impact the sensing characteristic canbe ascertained by reference and analysis to the archived manufacturingparameters and clinical test data.

FIG. 28B depicts a method 2810 for determining individualized sensingcharacteristics from at least a baseline sensing characteristic (or arepresentation thereof), such as that determined in method 2800. At2812, one or more manufacturing parameters are measured or otherwiseobtained from each medical device in a second multitude of medicaldevices. At 2814, an individualized sensing characteristic is determinedfrom at least one or more of the manufacturing parameters obtained instep 2812 and the baseline sensing characteristic, e.g., determined fromthe first multitude of medical devices. This can be performed, forexample, with a model such as those models described herein, and withthose manufacturing parameters identified as substantially impacting thebaseline sensing characteristic. Then, at 2816, individualizedcalibration information can be determined for each individual medicaldevice from at least the individualized sensing characteristicdetermined for that respective medical devices. This individualizedcalibration information can then be associated with the respectivemedical device as described elsewhere herein.

The second multitude of medical devices can be a portion of a productionlot or the entirety of a production lot, and in some embodiments can bemultiple production lots. Furthermore, in many embodiments theproduction lots can be manufactured and released for distribution tousers without regular in vitro testing or other testing of a baselinesubset from the production line that renders those devices in thebaseline subset unsuitable for distribution to users. Or, if suchtesting is not eliminated entirely, the amount of testing required foreach production lot or across multiple production lots can besignificantly reduced as compared to techniques where a baseline sensingcharacteristic is not determined directly from clinical data. In bothcases because such testing is reduced or eliminated, a correspondingincrease in production yield is obtained. The embodiments described withrespect to FIGS. 28A and 28B can be implemented with any of the in vivoor in vitro medical devices described herein.

FIG. 29A is a block diagram depicting an example embodiment of acomputer system 2900 that can be used to implement the calibrationembodiments described herein. Computer system 2900 is shown here as asingle system but can also be implemented in distributed fashion. System2900 can include an input port 2902, processing circuitry 2904,non-transitory memory 2906, and an output port 2908. Input port 2902 canbe communicatively coupled with processing circuitry 2904 and memory2906. Examples of data that can be supplied to input port 2902 include:the representations of manufacturing parameters 2910 collected during orafter the medical device manufacturing process, the in vitro test data2912 collected during in vitro testing of the baseline subset of medicaldevices. Other examples that are not shown can include data identifyingthe individual medical devices, data logs tracing the flow of eachmedical device through the manufacturing process and the medicaldevice's current location, identification of the production lot to whicheach medical device belongs, data identifying electronics to be usedwith the medical devices, assignments of particular medical devices toassociated electronics, and data logs tracing the flow of eachelectronics unit through the manufacturing process and the unit'scurrent location, to name a few. This input data can be stored withinmemory 2906 and read by processing circuitry 2904 by way of internal bus2914. Memory 2906 can also store software instructions that, whenexecuted by processing circuitry 2904, cause processing circuitry 2904to perform various steps, including all or a portion of the steps ofmaking determinations, estimations, calculations, use of models, use oftransfer functions, causing the storage of data, receiving data, andcausing the output of data described herein. For example, processingcircuitry 2904 can perform any and all of steps 2008 and 2009 of FIG.20A; 2018 and 2019 of FIG. 20B; 2018, 2019 and 2020 of FIG. 20C; 2702and 2705 of FIG. 27A; 2712, 2714, and 2715 of FIG. 27B; 2722, 2724, and2725 of FIG. 27C; 2753, 2754, 2755, 2756, 2758 and 2759 of FIG. 27D;2753, 2754, 2755, 2756, 2764, 2765 and 2759 of FIG. 27E; 2753, 2754,2755, 2756, 2774, 2775 and 2759 of FIG. 27F; 2806 of FIG. 28A; and 2814and 2816 of FIG. 28B.

Processing circuitry 2904 can determine the calibration information fromthe appropriate sensing characteristic in a number of ways. In someembodiments, one of a number of predetermined codes are identified thatmost closely approximate or match the sensing characteristic, such thatthe relatively large number of potential sensing characteristic valuescan be reduced to a more limited number of options without sacrificingsignificant performance. The predetermined code can be in the form ofthe sensing characteristic set itself, for example, if a slope of fiveis to be indicated, then the number five can be used as the calibrationinformation. In other embodiments, the predetermined code is analphanumeric value or string that does not indicate the calibrationinformation itself, but rather is set by system 2900 such that it can beused by the device (e.g., reader device, meter, sensor control device,etc.) to look up the corresponding calibration information, for exampleby reference to a translation matrix. In some embodiments, an in vivosensor and the on body electronics having that in vivo sensor'scalibration information stored in memory thereof can be provided inseparate packaging, in which case both the packaging for the in vivosensor and the packaging for the on body electronics can have thecalibration information or some other code printed thereon so that, incase the two are separated, the user can identify which sensor goes withwhich on body electronics.

Processing circuitry 2904 can also cause the output of determinedcalibration information (e.g., calibration codes) 2914 from output port2908. Processing circuitry 2904 can be implemented as a single discreteprocessor device or in distributed fashion as processing circuitryshared amongst multiple devices. Likewise, memory 2906 can beimplemented as a single discrete memory or multiple memories, or as asingle database or multiple databases, or combinations thereof. Memory2906 can be located on the same chip or device as other functionalcircuitry, including processing circuitry 2904. Memory 2906 can bepartially within computer system 2900 or distributed at other locations(such as separate databases) accessible by the manufacturer's network.

The individual medical devices can be traceable through themanufacturing process, such that the correlation of the manufacturingparameter with the individual medical device from which it was collectedis maintained. In some embodiments, each individual medical device canbe uniquely identifiable by an identifier physically associated with it.In certain examples of in vitro strips, the strips are manufactured on aprinted card or substrate and then subsequently separated into theindividual strips, and one identifier can be associated with that cardor substrate. Each strip can then be uniquely traced by the identifierof the card and data indicating the relative position of the strip onthat card.

The identifier can be in the form of a barcode, printed QR code, opticalcharacter recognizable (OCR) text such as an alphanumeric string, aresistive code (such as described in U.S. Publ. No. 2014/0200917, whichis incorporated by reference herein in its entirety and for allpurposes), a radio frequency (RF) readable device (e.g., an RFID elementor a Near Field Communication (NFC) element), or the like. Theidentifier (or a second identifier) can also identify the production lotwith which the medical device is associated. Each time the medicaldevice is subjected to a particular manufacturing stage and/or each timemanufacturing parameter data is obtained, the identifier is read and alog can be created (or an existing log retrieved and appended) with anindication of the current date and time, the identification of themanufacturing stage, the identity of manufacturing equipment used toprocess the medical device, the length of time medical device spends inthe manufacturing stage, and/or any manufacturing parameters that areobtained in relation to the processing of that medical device in thatparticular manufacturing stage.

FIGS. 29B-29D are block diagrams depicting conceptual process andinformation flows with respect to the manufacturing of biochemicalsensors. Although not limited to such, FIG. 29B is particularly suitedfor in vivo sensors. Referring first to FIG. 29B, section 2920 generallydepicts stages of manufacturing and collection of manufacturingparameter data. A group of medical devices (e.g., a production lot) isprocessed through a first manufacturing stage at 2922 and manufacturingparameters for the medical devices within the group are than measured orotherwise obtained at 2924. Depending on the type of manufacturingparameter being collected, step 2924 can occur concurrently withmanufacturing stage 2922 or afterwards. The group of medical devicesthen proceeds to a second manufacturing stage 2926, and againmanufacturing parameter data can be collected at 2928 eitherconcurrently or after conclusion of stage 2926. This process cancontinue through all manufacturing stages until, at 2930, constructionof the medical devices is complete, or completed to the point where invitro test data can be obtained. As manufacturing parameter data iscollected, e.g., at 2924 or 2928, that manufacturing parameter data canbe output to computer system 2900 for storage, as shown by informationpaths 2925 and 2929, respectively. The test or monitoring equipment thatobtains the manufacturing data can be communicatively coupled or linkedto computer system 2900 over a data network of the manufacturer.

In vitro testing of the baseline subset of medical devices is performedat 2932 and the resulting in vitro test data can be output viainformation path 2931 to computer system 2900. Again the equipment thatrecords the results of the in vitro testing can be communicativelycoupled with computer system 2900 over the data network. In alternativeembodiments (e.g., those described with respect to FIGS. 28A-28B) wherein vitro testing is not performed (or only minimally performed and notrelied upon in determining individualized calibration information), thein vitro testing at 2932 or the communication of in vitro test data overpath 2931 can be omitted in FIGS. 29B-D. In addition, the baselinesubset may be eliminated altogether and the distribution subset can bethe entirety of the production lot.

Computer system 2900 can then take the manufacturing parameter data andin vitro test data and determine the individualized calibrationinformation for each medical device in the distribution subset. Computersystem 2900 can assign each medical device in the distribution subset toa particular electronics unit (e.g., 1110). Alternatively, thisassignment task can be performed in another manner, manually orautomatically by manufacturing equipment, at another location within themanufacturing assembly line. The identity of the electronics unitassigned to each medical device can be communicated to computer system2900.

In some embodiments, the individualized calibration information isstored in the non-transitory memory of the electronics unit (e.g., thememory of on body electronics 1110) to which the individual medicaldevice is assigned. The individualized calibration information can beprovided by computer system 2900 to the device responsible for writingthe data within the non-transitory memory of the electronics unit asindicated by 2933. That data can then be written to the electronics unitat 2934 (e.g., a point of release stage), such as by wirelesslytransmitting to the electronics unit or inputting the data over a wiredaccess port, such as a universal serial bus (USB) port if available, oran internal data port, such as a serial boundary scan port. Theindividual medical device can then be packaged with the associatedelectronics unit to physically maintain the assigned relationship (thisstep can also be performed prior to writing the data to the electronicsunit). The final assembly can then be distributed to users at stage2940.

The devices can be distributed to the users in the form of a kit orpackage that can include one or more sensors. For example, in vivodevices can be distributed (e.g., sold) to users in a common packagingthat includes multiple (two, three, four, five, six, seven, eight, nine,ten, eleven, twelve, or more) in vivo sensors and their associatedelectronics units (e.g., sensor control devices). Each electronics unitcan have a non-transitory memory on which the individualized calibrationinformation is stored that is based on at least a measuredindividualized manufacturing parameter of the associated in vivo sensorand is specific to that associated in vivo sensor. In some embodiments,the in vivo sensor can be packaged separately from the associatedelectronics unit, which can also be packaged, with both packaged withinthe common packaging. In these embodiments some user assembly may beperformed prior to or concurrent with use.

FIG. 29C depicts a flow where the individualized calibration informationis output from system 2900 at 2943 and associated directly with themedical device itself at 2944, and is particularly applicable to medicaldevices such as in vitro test strips that do not have an electronicsunit already associated therewith. There are many approaches that can beemployed. In some embodiments, prior to leaving the manufacturingprocess, the individualized calibration information can be determinedand printed directly on the medical device, such as in the form of aprinted alphanumeric code, printed 2D barcode or 3D QR code, or a datamatrix code. A resistive code (such as described in the incorporatedU.S. Publ. No. 2014/0200917) can be placed on the medical device andread by circuitry on the meter. In other embodiments, the individualizedcalibration information can be associated with the medical device byattaching an RF tag (e.g., RFID or NFC) that has the calibrationinformation stored therein. In addition, ROM calibrators could be used,such as individual ones programmed to correspond to individual sensors.

As already described, in some embodiments in vitro strips can besegregated and grouped according to their individualized calibrationcodes, and then groups having the same calibration code can be packagedand sold as one unit. In these embodiments, the individualizedcalibration information can be associated directly with each individualstrip or associated with the packaging for the group of strips, e.g.,using any of the printed, RF, or ROM calibrator approaches described.

In order to program the code in the meter or other processing device,printed alphanumeric codes could be entered by the user, selected from alist of options provided to the user, or read by OCR by a camera on themeter or in the strip port (so that they can be read automatically uponstrip insertion). Similar camera-based or bar-code based approachescould be employed for QR codes or printed barcodes or data matrix codes.If RF tags (e.g., RFID or NFC) are used, then the meter or processingdevice would include an RF tag reader, which could potentially beincluded in the strip port for automatic reading upon strip insertion.One such approach is described in U.S. Pat. No. 8,115,635, which isincorporated by reference herein in its entirety for all purposes. Inother examples, ROM calibrators can be used. In some examples, acomputing device, such as a mobile phone, can obtain the calibrationinformation using one of the aforementioned techniques (e.g., opticalscan, NFC or RFID communication, etc.) and a meter can include Bluetoothcommunication circuitry and establish a Bluetooth link with thecomputing device. The obtained calibration information can betransferred from the computing device to the meter over the Bluetoothlink. In another example, the computing device such as a mobile phonecan obtain the calibration information from a server (via the cloud, asdescribed with respect to FIG. 29D below) if the computing device hasthe identifier for the in vitro medical device (which can also beobtained by one of the aforementioned techniques) and communicates it tothe server, and then after receiving the calibration information thecomputing device can transfer it to the meter over the Bluetooth link.

FIG. 29D depicts an example embodiment where the calibration informationcan be provided to a processing device 2949 in the field that is beingused to process biochemical data collected by the individual medicaldevice after its distribution. For example, a reader device, a meter, orother processing device can obtain the identifier of the individualmedical device. If that individual medical device has an associatedelectronics unit, then the identifier can be requesting from orotherwise provided by the electronics unit (e.g., 1110). Otherwise, theidentifier can be obtained directly from the medical device, such as bya user manually reading the identifier from the medical device or itspackaging and inputting it into the processing device 2949, or theprocessing device 2949 can read the identifier from the medical deviceor the packaging in one of the manners already described. At 2950, theprocessing device 2949 can transmit the identifier to computer system2900 (or a trusted server) over the Internet or a cloud network 2942.Computer system 2900 can read the identifier, select the appropriateindividualized calibration information, and output, at 2954, thatcalibration information back to the processing device 2949, which canthen algorithmically process the data collected by the medical deviceand render it to the user via a display (or output to another device).

Improvements Related to Calibration

Studies have confirmed that the calibration embodiments described hereinresult in tangible improvements in the accuracy of biochemical sensingmeasurements made by the medical devices. This represents an improvementin the operation of the calibrated medical devices themselves, andfurther results in an improvement in the operation of the monitoringsystems and monitoring devices incorporating these medical devices, aswell as an improvement in the operation of the computing devices thatprocess or otherwise utilize the improved accuracy data produced by thecalibrated medical devices. Improvements through lessening variationsbetween medical devices were also confirmed, as were improvements to themanufacturing yield of the medical devices. These and other improvementsconstitute grounds upon which the present subject matter is patenteligible, such as under 35 U.S.C. section 101 in the United States andsimilar requirements in other jurisdictions.

For example, studies of in vivo analyte sensors were conducted thatexplored relationships between the in vivo glucose sensitivities ofthose sensors obtained through clinical studies, and variousmanufacturing parameters collected during manufacturing of those samesensors. Subjects in the clinical studies were asked to take an in vivomeasurement with an implanted in vivo sensor immediately afterperforming a blood glucose (BG) reference test using a finger stick andtest strip. The relative bias between the BG reference test and thesubsequent in vivo sensor reading was modeled against the variousmanufacturing parameters for that in vivo sensor. Correlation(traceability) between the clinical data and the manufacturing data wasmaintained using lot reports, unique identifiers for the in vivo sensor,and unique identifiers for the in vivo systems incorporating thatsensor.

Various statistically significant associations were identified. FIGS.30A-30B are plots depicting example data sets demonstratingstatistically significant associations between in vivo results andmanufacturing parameters. FIG. 30A depicts, on the y-axis, a relativebias between in vivo readings and corresponding in vitro blood glucose(BG) measurements plotted against, on the x-axis, a representation ofthe area of the sensing region (e.g., mm²) for each of the sensorsstudied. More particularly, the x-axis indicates the relative differencein area between each individual sensor and a central tendency of theproduction lot from which it came. FIG. 30A indicates a positivecorrelation between sensing area and in vivo sensitivity, such that arelatively larger sensing area correlates to a relatively higher in vivosensitivity, while a relatively lower sensing area correlates to arelatively lower in vivo sensitivity.

FIG. 30B depicts, on the y-axis, the relative bias between in vivoreadings and corresponding in vitro blood glucose (BG) measurementsplotted against, on the x-axis, a representation of the thickness of themembrane (e.g., μm) for each of the sensors studied. In this example,the total lateral thickness of the sensor is measured at multiplelocations at and near the sensing region and an average value isdetermined. A representative value for the sensor thickness beneath themembrane (e.g., a nominal substrate thickness) is then subtracted fromthe average value to provide the average membrane thickness for eachparticular sensor, which was then used as the representation of thethickness of the membrane. FIG. 30B indicates a negative correlationbetween membrane thickness and in vivo sensitivity, such that arelatively larger membrane thickness correlates to a relatively lower invivo sensitivity, while a relatively lower membrane thickness correlatesto a relatively higher in vivo sensitivity.

Individualized calibration information was determined (sensitivityslopes in this example) for the sensors used in the clinical studiesusing both sensing area and membrane thickness as the manufacturingparameters. The clinical studies were reanalyzed using each sensor'sindividualized calibration information rather than a lot levelcalibration code. The reanalysis showed that the difference in meanabsolute relative difference (MARD) by lot improved using theindividualized calibration information. The reanalysis also showed thatthe total standard deviation of relative difference between sensors alsoimproved using the individualized calibration information. In addition,the mean relative difference (MRD), or precision performance, alsoimproved.

An additional study was conducted using sensors from a single lot thatwere divided into three groups: a first group where the individualizedcalibration information represents a relatively high predicted in vivosensitivity, a second group where the individualized calibrationinformation represents relatively low predicted in vivo sensitivity, andthird group where the individualized calibration information representsa median or moderate predicted in vivo sensitivity between the first andsecond groups. In this study the sensors from the three groups were usedby subjects and the accuracy of the resulting data was analyzed andcompared to data from sensors that were factory calibrated on alot-level basis. FIGS. 31A-31B are plots depicting sample data sets usedin the study, with MRD on the y axis and glucose level (mg/dL) on the Xaxis. FIG. 31A depicts the MRD for each of the three groups when thelot-level calibration information was used and FIG. 31B depicts the MRDfor each of the three groups when the individualized, sensor-levelcalibration information was used. As can be seen here, use of theindividualized calibration information minimized the performancevariation across the production lot and also resulted in an improvementin MARD.

Use of the individualized calibration information resulted in animprovement in production yield. Use of the individualized calibrationinformation was found to improve between sensor variation (e.g.,sensor-to-sensor variation) within a production lot by substantiallylowering it and thus permitting more medical devices to pass tests forsensitivity precision. Utilizing the embodiments of individualizedcalibration information, an improvement in precision performance ofgreater than 20% has been obtained.

Still other statistically significant associations are possible and candepend upon the specifics of the design of the medical device and theassociated manufacturing process. Some embodiments of medical deviceswithin the scope of the present disclosure may have a sensing regiondifferent from that described herein, and may have membrane differentfrom that described herein, or may lack a membrane altogether. Becausethe present subject matter is not limited to any one design ormanufacturing process, it is likely and indeed expected that otherstatistically significant associations will exist for different designsand processes. Those of ordinary skill in the art will readily recognizethat the present subject matter is not limited to determiningindividualized calibration information using only a size of the sensingregion and or size of the membrane.

In addition, the models used in the example embodiments herein can becontinually refined to capture variability not explained by the model.When in vivo or in vitro sensors are in vitro tested and have theirpredicted in vitro sensing characteristic (e.g., SC_(MD)) determined, aresidual sensing characteristic can be calculated. In some embodimentsthis residual sensing characteristic (SC_(R)) can be determinedaccording to (5):

SC_(R)=(Actual In Vitro SC−SC_(MD))+Lot Level In Vitro SC

Here, the lot-level in vitro sensing characteristic (SC) can be acentral tendency and can be for the baseline subset, e.g., the baselinesensing characteristic SC_(B). As described before, the evaluatedsensing characteristic can be the sensitivity or an aspect thereof(e.g., slope or intercept). The residual sensing characteristic looks atthe differences between the observed and predicted sensingcharacteristics from the model and shows the level of variability notexplained by manufacturing parameters within the model. Thesedifferences can be evaluated as variability around the lot level invitro sensing characteristic and thus indicates a measure of how muchvariation is unexplained by the model.

While many embodiments have been described with respect to sensors forbiochemical attributes, the embodiments can also be applicable tosensors for other physiological attributes as well. Also, while manyembodiments have been described with respect to determining or utilizingcalibration information, the embodiments can also be applicable todetermine or utilize other types of information that characterizes themedical device.

Example Embodiments of Modifying a Surface of a Sensor Substrate

Embodiments are also set forth herein that relate to modifying a surfaceof a sensor substrate to assist in positioning of a sensing element (orportion thereof) on the sensor surface. While not limited to such, theseembodiments can be particularly useful when applying a liquid to thesensor surface to form the sensing element. Electromagnetic radiationand/or mechanical force can be applied to a surface to modify thesurface in a particular area or location. That modified area can affecthow the liquid disperses or gathers on the surface. When used in thefabrication of a sensor, this technique can permit more accurate andprecise sizing (e.g., area and/or depth) and positioning of sensingelements produced during manufacturing. It also reduces the variabilityin size and location of each sensing element as compared to one or moreother sensing elements on the same sensor and/or sensing elements ofother sensors. This, in turn, can lead to reduced variation insensitivities between sensors, and thus more accurate, precise, andconsistent analyte measurements for users.

FIGS. 32A-32F are schematic diagrams depicting various exampleembodiments of a portion of a sensor substrate 3202 at various stagesduring manufacture of a sensing element. Substrate 3202 can be, forexample, on insertion tip 530 of the embodiment of sensor 500 describedwith respect to FIG. 5A, or can be part of any of the other embodimentsof in vivo and in vitro sensors described herein (e.g., the embodimentsdescribed with respect to FIGS. 4, 5B, 6-10C, 15A-17, and 21A-25B).

A liquid or liquid agent is applied to the substrate to form the sensingelement. This liquid agent can have an electrochemical characteristicthat detects or assists in detection of the analyte (e.g., glucose) andcan be referred to as an electrochemical agent. The electrochemicalagent can be a solution, such as water-based or otherwise. Embodimentsof the surface modification technique can be used with other agents aswell, such as agents that form a sensor membrane, treating agents,adjuvants, secondary electrochemical agents, fixing agents (e.g., acrosslinker), or others. FIG. 32A depicts substrate 3202 prior tomodification. Substrate 3202 can be any portion of a sensor upon whichplacement of a sensing element is desired, e.g., a base, a coating orlayer on a base, an electrode, and the like.

FIG. 32B depicts substrate 3202 after modification of area 3204 by theapplication of electromagnetic radiation. Application of theelectromagnetic radiation may result in a change to the visibleappearance of substrate 3202, although not always. In this example, area3204 has a ring-like shape formed by inner and outer boundaries 3205 and3206, which in this embodiment are concentric circles, separated by adistance 3207. Other shapes can also be used (as described furtherbelow). Inner boundary 3205 defines an unmodified interior 3208 of area3204, which is the target area for placement of the sensing element. Thearea of substrate 3202 beyond outer boundary 3206 is also unmodified.

Application of the electromagnetic radiation modifies a surfacecharacteristic of the substrate in area 3204 as compared to the adjacentareas that were not exposed to the electromagnetic radiation. Thesurface characteristic can affect the mobility of the liquid in variousways. For example, the modified surface characteristic can be such thatthe liquid is attracted to the modified area even when the liquid is notin direct contact with the modified area (e.g., a liquid on the surfacebut not in contact with the modified area can move towards the modifiedarea). Such a modified surface characteristic can also cause or increaseattraction between the liquid and the modified area when in directcontact as compared to an unmodified area (e.g., a philic characteristicthat facilitates spreading of the liquid across the modified area).Although the modified and unmodified surface characteristics are suchthat the liquid moves towards the modified area, the liquid may proceedonly to the boundary of the modified area and not move over the modifiedarea itself (see, e.g., FIG. 32D). If the magnitude of the surfacecharacteristic is increased, such as by application of a relativelyhigher power (an example of one of various factors that can control thecharacteristic), then in such embodiments the liquid can move towardsand over the modified area (see, e.g., FIG. 32E).

In other examples, the modified surface characteristic can be such thatthe liquid is repelled by the modified area even when the liquid is notin direct contact with the modified area (e.g., a liquid placed in alocation not in contact with the modified area can move away from themodified area; see, e.g., FIG. 32F). Such a characteristic can alsocause or increase repulsion (or decrease attraction) between the liquidand the modified area when in direct contact as compared to anunmodified area (e.g., a phobic characteristic that causes beading ofthe liquid or impedes spreading across the modified area). Further, acombination of these techniques can be used. For example, multiplemodified areas can be created with opposing characteristics to cause theliquid to move from a first modified area to a second modified area(that also acts as a target area).

FIG. 32C depicts substrate 3202 at a moment immediately afterapplication of the liquid 3209. Here, liquid 3209 has been applied to anarea in the interior of area 3204 that is smaller than that defined byinner boundary 3205. The shape of the applied liquid at this time can beirregular and off-center. FIG. 32D depicts substrate 3202 after liquid3209 has dispersed on the surface of substrate 3202. In this embodiment,the modification to area 3204 attracts liquid 3209 and causes liquid3209 to disperse or spread out across the entire unmodified interior3208 up to inner boundary 3205, where the dispersion ceases. The borderof the dispersed liquid 3209 generally aligns with inner boundary 3205.Liquid 3209 can then dry and form a relatively uniform sensing elementacross interior region 3208 for the sensor.

FIG. 32E depicts another example embodiment of substrate 3202 afterapplication of liquid 3209 as shown in FIG. 32C. In this embodiment, themodification to area 3204 attracts liquid 3209 and causes liquid 3209 tospread out across the entire interior 3208 of area 3204 (as depicted inFIG. 32D) but also past inner boundary 3205 to outer boundary 3206,where the dispersion ceases. The border of the dispersed liquid 3209generally aligns with outer boundary 3206. Liquid 3209 can then dry andform a relatively uniform sensing element across both interior region3208 and modified area 3204.

FIG. 32F depicts another example embodiment of substrate 3202 afterapplication of liquid 3209 as shown in FIG. 32C. In this embodiment, themodification to area 3204 repels liquid 3209 and causes liquid 3209 tomove to the center of interior 3208, where it forms a bead oraccumulation. In this embodiment, the target area is the area on whichliquid 3209 is present, which is in proximity to modified area 3204 butneither on nor immediately adjacent to (i.e., bordering) modified area3204. Liquid 3209 can then dry and form a sensing element in this centerarea.

The types of electromagnetic radiation used for surface modification canvary, as can the surface compositions themselves. FIGS. 33A and 33B arephotographs depicting example embodiments of substrates 3202 having aseries of ring-like surface modifications 3204-1, 3204-2, and 3204-3formed by the application of laser radiation. Various frequencies oflaser radiation can be used to accomplish the surface modification, suchas ultraviolet, visible, and infrared. FIG. 33A is a photograph of thelaser modification to a bare polyethylene terephthalate (PET) substrate3202. FIG. 33B is a photograph of the laser modification to a carbonprinted PET substrate 3202, where the outline of the middle area 3204-2has been annotated for ease of visibility. Substrates such asultraviolet (UV) curable dielectrics (and others) can also be used.

In the samples depicted in both FIGS. 33A-B, the surface modification toone ring-shaped region 3204 was performed by directing the laser at thesubstrate in five adjacent circles of progressively increasing diameter.Each adjacent circle was created by pulsing the laser at discrete spotsarranged in a circular pattern, although the adjacent circles (or theentire ring-shaped region itself) can be created by continuousnon-pulsed application of the laser, with or without adjacent circles.Applied power, wavelength, and duration of application of the laser cangenerally be used to modify the surface characteristic (e.g., whether itattracts or repels and by how much). In pulsed embodiments, the size ofa pulsed spot and the spacing between pulsed spots can also be used tomodify the surface characteristic. The size of a spot can be controlledby focal length of the lens, the laser wavelength, the distance fromlens to the working surface, and the laser pulse energy. Similartechniques can be used to create the other shapes of region 3204described herein. These regions 3204 can also be generated in othermanners using laser or non-laser sources.

FIGS. 34A and 34B are photographs depicting an example embodiment of acarbon printed PET substrate 3202 with a series of six modified areas3204-1 through 3204-6. FIG. 34A shows substrate 3202 prior to dispensingan electrochemical agent, where unmodified interior regions 3208-1through 3208-6 are bare. FIG. 34B shows substrate 3202 after dispense ofindividual drops of the electrochemical agent into interior regions 3208by a piezoelectric nozzle. Here, the interior regions are now covered bythe electrochemical agent to form sensing elements 3209-1 through3209-6. As can be seen in FIG. 34B, the border of elements 3209 closelyaligns with the interior boundary of modified areas 3204, and eachelement 3209 has the same or similar size and shape. Although theembodiments described herein are not limited to such, the modifiedsurface characteristics for the embodiment of FIGS. 34A-34B weregenerated at approximately 50-60 milliwatts (mW), measured in a positionnear-equivalent to the surface itself, with an approximately 340-350nanometer (nm) wavelength laser. Different wavelength lasers (havingwavelengths greater or less than 340-350 nm) and different powers(greater or less than 50-60 mW) can also be used to achieve the surfacecharacteristics described herein. Different wavelengths will typicallyrequire different powers to achieve the same effect.

Although the embodiments described herein are not limited to such, eachelement 3209 in FIG. 34B is generally circular with a nominal diameterof 170 microns and each element 3209 is nominally 250 microns apart(center to center). As mentioned, modified area 3204 can have othersizes and shapes. FIG. 35A is a schematic view of an example embodimentwhere modified area 3204 is shaped as a solid circle. In thisembodiment, area 3204 can be modified so as to attract the liquid suchthat the target area for the sensing element is area 3204. Instead of asolid circle, other shapes can also be used, such as a solid ellipse, asolid polygon (e.g., triangle, square, rectangle, trapezoid, pentagon,hexagon, etc.) with rounded or sharp corners, or a combination thereof(e.g., a D-shape). Similarly, ring-shaped area 3204 need not be formedfrom concentric circles, and can instead be formed by ellipses, polygons(e.g., triangle, square, rectangle, trapezoid, pentagon, hexagon, etc.)with rounded or sharp corners, or a combination thereof (e.g., aD-shape), where the inner and outer boundaries are concentric oreccentric. By way of example, FIG. 35B depicts an embodiment wherering-shaped region 3204 is formed by concentric ellipses, and FIG. 35Cdepicts an embodiment where ring-shaped region 3204 is formed byconcentric squares. Whether in the form of a ring or solid shape, themodified area 3204 can be configured such that it is or is part of thetarget area (the area in which the liquid agent comes to rest) or themodified area 3204 can be configured such that an adjacent area ornon-adjacent area in close proximity (see, e.g., FIG. 32F) is the targetarea. In addition, if multiple sensing elements are present on asubstrate, then those elements can be arranged in any desired pattern orgrid (e.g., with one or more rows and/or one or more columns). FIG. 35Ddepicts an example embodiment where the sensing elements are solidcircles arranged in an X-shaped grid.

FIG. 36A is a flow diagram depicting an example embodiment of a method3600 of manufacturing a sensor by modifying a surface withelectromagnetic radiation. At 3602, the method includes modifying anarea of a surface of a sensor substrate with electromagnetic radiationto create a modified area. Then, at 3604, the method includes applying aliquid to the surface of the sensor substrate such that the liquid comesto rest in a target area on the surface, where the target area isdetermined at least in part by the location of the modified area. Steps3602 and 3604 can be repeated as necessary to form one single sensingelement, or can be repeated to form multiple sensing elements atdifferent locations on the substrate.

The magnitude of the modified surface characteristic can be timedependent, such that the characteristic degrades after modification.Thus, it can be beneficial to perform liquid application step 3604relatively quickly after modification step 3602 during the time when themodified surface characteristic remains adequately present. While notlimited to such, step 3604 should be performed within twenty-four hoursof step 3602. In many embodiments step 3604 is performed within severalhours of step 3602, and in some embodiments step 3604 is performedwithin one hour or less of step 3602, preferably within ten or fifteenminutes.

If desired, the application of liquid in step 3604 can occur in one ormore iterations. For example, the liquid can be applied as a sequence oftwo or more drops where the drops are applied to form one sensingelement before proceeding to a next sensing element (on the same ordifferent substrate). In examples where multiple sensing elements arepresent on one substrate, then a first drop of the liquid can be appliedto each sensing element (sometimes referred to as a pass) and then asecond drop can be applied to each sensing element (e.g., a second pass)and the passes can be repeated until the desired number of drops areapplied to each sensing element on the substrate. Alternatively, eachpass can include the application of multiple drops to each sensingelement, and multiple such passes can be used. In some embodiments, themultiple drops (either in one pass or in sequential passes) can beapplied to different locations to form one sensing element. Such anapproach can be useful for: sensing elements that are relatively largeas compared to the volume of the drop; sensing elements that have alongitudinal axis (e.g., as in an embodiment similar to FIG. 32B wherethe sensing element is formed in the interior of the elliptical ring,and drops are placed at different locations along the long axis of theelliptical ring (between left and right in the figure)); sensingelements in a ring-shape where drops are placed in a ring-shaped patternalong the surface of the ring-shape; or others.

FIG. 36B is a flow diagram depicting another example embodiment ofmethod 3600 where the electromagnetic radiation is laser radiation.Method 3600 utilizes a laser marking system that may, in someembodiments, include a user interface, alignment optics, controlhardware and software, a power source, and the laser. At 3612, a size ofthe modified area can be entered into the laser marking system. This maybe performed for each marking, or may be performed once for a productionrun of many sensors. At 3614, the laser marking system can focus (and/oralign at the proper location) on a substrate of a sensor. At 3616, thelaser marking system can radiate a laser to create a modified area onthe substrate. This may involve multiple activations of the lasermarking system (e.g., when using laser pulses, or when creating multiplesensing elements where each is created with the continuous applicationof the laser, etc.), where each activation also includes a step offocusing 3614. The resulting modified area can have a modified surfacecharacteristic as compared to one or more adjacent areas, and thismodified characteristic may act to attract or repel an electrochemicalagent as desired. Modification of the surface characteristic betweenthose that cause relative attraction to those that cause relativerepulsion can be accomplished, in some embodiments, by adjustment ofmodulation of the laser power and focus height. At 3618, if two or moremodified areas are to be created on a single substrate, then either thesubstrate or the laser can be moved and step 3616 (and optionally step3614) can be repeated to create the next modified area. At 3620, thesubstrate can be moved to an electrochemical dispersion system, and theelectrochemical agent can be deposited (e.g., in the form of one or moredrops dispensed from a nozzle) to a target area defined by each modifiedarea. As described this can occur within a few hours or less of themodification step(s). The liquid can then be dried and transferred tothe next manufacturing stage (e.g., application of a membrane, etc.).

Another technique for modifying a surface of a sensor substrate is toapply mechanical force to the substrate to create a well, indentation,impression for placement of a sensing element. FIGS. 37A and 37B are topdown views of an example embodiment of a substrate 3702 before and aftercreation of a well 3704. Substrate 3702 can be, for example, oninsertion tip 530 of the embodiment of sensor 500 described with respectto FIG. 5A, or can be part of any of the other embodiments of in vivoand in vitro sensors described herein (e.g., the embodiments describedwith respect to FIGS. 4, 5B, 6-10C, 15A-17, and 21A-25 ).

In FIG. 37B, well 3704 has a round, more specifically circular, top downprofile. FIG. 37C is a cross-section of substrate 3702 taken across line37C-37C of FIG. 37B, and shows that, in this embodiment, well 3704includes a flat bottom surface 3706 with a sidewall 3708 that isperpendicular to bottom surface 3706. Well 3704 has a depth 3709measured between bottom surface 3706 and surface 3710 of substrate 3702adjacent to well 3704. In this configuration, well 3704 has a generallycylindrical interior space, where the height of the cylinder is height3709.

While the top-down profile of well 3704 is circular, other top downprofile shapes can be used for well 3704 including, but not limited to:an ellipse, a polygon (e.g., triangle, square, rectangle, trapezoid,pentagon, hexagon, etc.) with rounded or sharp corners, or a combinationthereof (e.g., a D-shape). Further, for each of the top-down profileshapes, different side profile shapes can be implemented. In FIG. 37C,well 3704 has a generally rectangular side profile, but in otherembodiments the side profile can be a partial circle (e.g., asemi-circle), a partial ellipse, other polygonal or partially polygonalshapes (e.g., square, trapezoid, five-sided shape, etc.) with square orrounded corners, and combinations thereof (e.g., D-shaped). FIG. 37D-37Fare cross-sectional views of other embodiments of wells 3704 havingcircular top-down profiles such as that depicted in FIG. 37B, but with:a five-sided shape (e.g., partial hexagon) (FIG. 37D), a D-shape (FIG.37E), and a partial elliptical shape where surface 3706 is both a bottomand side surface (FIG. 37F).

FIG. 37G is a top down view of another example embodiment of a well 3704and FIG. 37H is a cross-section taken along line 37H-37H of FIG. 3G.Here, angle 3712 between bottom 3706 and sidewall 3708 is approximately120 degrees although any obtuse angle less than 180 degrees can be used.The presence of the sloped sidewall 3708 gives well 3704 a top downprofile appearance of two concentric circles.

For any of these shapes and configurations, well 3704 can be filled witha liquid (e.g., electrochemical agent) that can be dried and used as asensing element. FIGS. 38A-38D are cross-sections depicting the exampleembodiment of FIG. 37C with different fill levels. In the embodiment ofFIG. 38A, well 3704 is under-filled, and sensing element 3209 onlypartially covers bottom surface 3706. In the embodiment of FIG. 38B,well 3704 is under-filled, and sensing element 3209 covers the entirebottom surface 3706, but fills only part of the depth 3709 of well 3704(e.g., sensing element 3209 has a height that is less than depth 3709).Element 3209 is in contact with, or substantially in contact with,sidewall 3708. In other embodiments, element 3209 can reside mainly onone side of bottom surface 3706 (without covering the entire bottomsurface 3706) and also be in contact, or substantially in contact, withsidewall 3708 on that one side of well 3704. In the embodiment of FIG.38C, sensing element 3209 covers the entire bottom surface 3706, fillsthe entire depth 3709 of well 3704, and is flush with substrate surface3710 (e.g., sensing element 3209 has a height that is equal to depth3709). In the embodiment of FIG. 38D, well 3704 is over-filled, andsensing element 3209 fills the entire depth 3709 of well 3704 andextends to a height greater than substrate surface 3710 (e.g., sensingelement 3209 has a height that is greater than depth 3709).

The size and shape of the well corresponds to the size and shape of theportion of the tool that forces into the substrate, e.g., a cylindricaltool will create a reverse or negative impression and produce acylindrical well of the same size. FIG. 39A is a photograph of anexample embodiment of a tool 3900 for creating wells. This tool can bereferred to as a tamping instrument. Tool 3900 includes a shaft 3902movable up and down in the Z direction. Shaft 3902 has an end portion3904 that is shown in greater detail in the photograph of FIG. 39B. Endportion 3904 tapers to a tip 3906 with a generally flat bottom surface.End portion 3904 and tip 3906 will create a well similar to thatdescribed with respect to FIGS. 37G-37H, where the slope of the taperdetermines the slope of sidewall 3708. Force applied to shaft 3902 willcause shaft 3902 to move downwards into a substrate (not shown) tocreate the well. While various types of sources can be used to apply theforce, in this embodiment a coil spring 3908 is compressed and appliesforce against the large cylinder of shaft 3902 (see arrow in FIG. 39A).Tool 3900 can also include a user interface, alignment optics, controlhardware and software, and a power source.

The well depth depends on the size of tip 3906, the spring constant, thedegree of compression of spring 3908, and how far tip 3906 is from thesubstrate prior to releasing the compressed spring 3908. If a taperedtip 3906 is used, then the well diameter is dependent upon these factorsas well. In other embodiments, pneumatic force, electrically generatedforce, and others force generating devices can be used.

FIGS. 40A and 40B are top down photographs depicting example embodimentsof wells 3704 produced with tool 3900. The photographs are at comparablemagnification and illustrate two examples of different size wells thatcan be produced by varying the aforementioned factors. In FIG. 40A, well3704 has a diameter of approximately 152 microns, and in FIG. 40B well3704 has a diameter of approximately 267 microns. In general, thistechnique can be used to create wells of any desired size, depending onthe dimensions of the tamping instrument and the number of consistentsized tamping iterations the instrument will be used for (e.g.,factoring in wear).

FIG. 41A is a top down photograph depicting an example embodiment of awell 3704 formed with tool 3900 to a depth of approximately five micronsprior to application of the electrochemical agent. FIG. 41B is a topdown photograph depicting the example embodiment of FIG. 41A afterdispensing the electrochemical agent 3209 over bottom surface 3706 andpartially filling well 3704. FIGS. 42A and 42B are top down photographsdepicting an example embodiment of a well 3704 formed with tool 3900 toa depth of approximately fifteen microns prior to dispense and afterpartial filling with agent 3209, respectively. As can be seen in FIGS.41B and 42B, the shape of agent 3209 closely approximates the circularprofiles of the wells 3704.

It has been found that the use of wells is effective in improvingaccuracy of the size of sensing elements and in improving accuracy oftheir placement. A significant decrease in the coefficient ofvariability across sensing elements on the same and different sensorsubstrates was observed. FIG. 43 is a series of photographs showingthese improvements. A number of substrates were used, and on eachsubstrate the liquid agent was dispensed in two locations (spot 1 andspot 2) separated by a distance. In the “control” cases no well wascreated and the liquid was dispensed directly on the unmodifiedsubstrate surface. In the “well” cases two wells were created (one atspot 1 and one at spot 2) and the liquid agent was dispensed therein. Ascan be seen by the photographs, the dispensed agent in the “well” caseshave more uniform borders and less variation in size than those in the“control cases.”

FIG. 44A is a flow diagram depicting an example embodiment of a method4400 of manufacturing a sensor by creating a well for a sensing element.At 3602, a well is created in a sensor substrate. Then, at 3604, aliquid is applied into the well in the sensor substrate such that theliquid comes to rest in the well.

FIG. 44B is a flow diagram depicting another example embodiment ofmethod 4400. At 4412, a size of the well can be entered into a userinterface of the well creation tool (e.g., tool 3900). This may beperformed for each marking, or may be performed once for a productionrun of many sensors. At 4414, the well creation tool can focus and/oralign to the proper location on a substrate of a sensor. At 4416, thewell creation tool can apply a mechanical force to create the well. Thismay involve one or more downward strikes, where each downward strike caninclude a step of alignment 4414. At 4418, if two or more wells are tobe created on a single substrate, then either the substrate or the toolcan be moved and step 4416 (and optionally step 4414) can be repeated tocreate the next well. At 4420, the substrate can be moved to anelectrochemical dispersion system, and the electrochemical agent can bedeposited (e.g., in the form of one or more drops dispensed from anozzle) to each well in the substrate. The liquid can then be dried andtransferred to the next manufacturing stage (e.g., application of amembrane, etc.).

While the creation of wells has been described primarily by theapplication of mechanical force, in other embodiments the wells can becreated in other ways, such as with photolithography, laser orelectrical etching or ablation, and others.

In some example embodiments, the sensor substrate can be modified withboth a well and with a radiation treated surface. For example, referringback to FIGS. 37B-H, any of the bottom surfaces 3706, sidewall surfaces3708, top substrate surfaces 3710, and/or combinations thereof can bemodified with radiation to alter the liquid mobility characteristic,e.g., to either increase or decrease the mobility as compared tounmodified adjacent surfaces. For example, a ring-shaped modified area(e.g., 3204 of FIG. 32B) can be created around bottom surface 3706,where the ring-shaped area is just sidewall surface 3708, or is just topsurface 3710 bordering the perimeter of well 3704, or both. In anotherexample, a ring-shaped modified area can be placed around the perimeterof bottom surface 3706 (or a portion thereof). In yet another example,the entirety of bottom surface 3706 can be modified to attract theagent.

Furthermore, all of the embodiments of surface modification (e.g., withradiation and/or the creation of wells) can be combined all of thecalibration embodiments described herein. Such combinations can furtherenhance those improvements related to calibration already discussedherein. For example, the description of manufacturing parameters hereincan also apply to the size or dimension of the modified area, the targetarea, the well, and/or a sensing element (in liquid or dried form)applied to the modified area, target area, and/or well. To the extentmultiple sensing elements are applied to a single substrate, themanufacturing parameter can be representative of any or all such sensingelements (e.g., a total area). By way of non-limiting example, ameasured manufacturing parameter can be the area of interior space 3208of ring-shaped area 3204 of FIG. 32B, the area of ring-shaped area 3204(FIG. 32B), the diameter or circumference of inner or outer boundaries3205 and 3206 (FIG. 32B), the diameter, circumference or area of bottomsurface 3706 of well 3704 (FIGS. 37B-37H), the measured or estimatedvolume of sensing element 3209 within well 3704, and others. Those ofordinary skill in the art, upon reading this description, will readilyrecognize the many different manufacturing parameters that can bemeasured in relation to modified areas, target areas, wells, and sensingelements. In some cases, the reduction in variation resulting from useof modified areas and wells can decrease the significance of the size ofthe sensing region as a manufacturing parameter for individualizedcalibration, allowing the calibration to utilize other measurements likemembrane thickness and exclude the size of the sensing region.

The embodiments described herein are restated and expanded upon in thefollowing paragraphs without explicit reference to the figures. In manyexample embodiments, a method for calibrating individual medical devicesis provided that includes: at least partially manufacturing a multitudeof medical devices, the multitude including a first subset and a secondsubset, where each of the medical devices in the multitude are adaptedto sense a biochemical attribute; measuring an individualizedmanufacturing parameter of each medical device in the multitude;determining, with processing circuitry, an in vitro sensingcharacteristic of the first subset from data obtained by in vitrotesting the first subset; and determining, with processing circuitry,individualized calibration information for each medical device in thesecond subset using at least a representation of the individualizedmanufacturing parameter for each medical device and a representation ofthe in vitro sensing characteristic of the first subset of medicaldevices, where the medical devices in the first subset are differentfrom the medical devices in the second subset.

In some embodiments, each of the medical devices in the multitude is ananalyte sensor and the biochemical attribute is a level of an analyte.Further, each analyte sensor in the multitude can be adapted to sensethe analyte level in vivo, and the in vitro sensing characteristic canbe an in vitro sensitivity to the analyte.

In some embodiments, each of the analyte sensors in the multitudeincludes a sensing region, optionally where the individualizedmanufacturing parameter is a size of the sensing region. In certainembodiments, the size of the sensing region is representative of atleast one of the following: a width of the sensing region, a length ofthe sensing region, a thickness of the sensing region, a peripherallength of the sensing region, an area of the sensing region, or a volumeof the sensing region. In certain embodiments, the representation of theindividualized manufacturing parameter for a respective analyte sensorin the second subset is a deviation of the size of the sensing region ofthe respective analyte sensor from a central tendency of a size of thesensing region for the multitude of analyte sensors.

In some embodiments, each of the analyte sensors in the multitudeincludes a membrane for the sensing region, optionally where theindividualized manufacturing parameter is a size of the membrane. Incertain embodiments, the size of the membrane is representative of atleast one of the following: a width of the membrane, a length of themembrane, a thickness of the membrane, a peripheral length of themembrane, an area of the membrane, or a volume of the membrane. Incertain embodiments, the representation of the individualizedmanufacturing parameter for a respective analyte sensor in the secondsubset is a deviation of the size of the membrane of the respectiveanalyte sensor from a central tendency of a size of the membrane for themultitude of analyte sensors.

In some embodiments, each of the analyte sensors in the multitudeincludes a sensing region and a membrane for the sensing region,optionally where measuring an individualized manufacturing parameter ofeach analyte sensor in the multitude includes measuring a size of thesensing region and a size of the membrane of each analyte sensor. Incertain embodiments, the individualized calibration information for eachanalyte sensor in the second subset is determined using: arepresentation of the size of the sensing region of a respective analytesensor in the second subset; a representation of the size of themembrane of the respective analyte sensor in the second subset; and arepresentation of the in vitro sensitivity of the first subset. Incertain embodiments, the representation of the in vitro sensitivity caninclude a slope of a central tendency of in vitro sensitivity of thefirst subset, an intercept of a central tendency of in vitro sensitivityof the first subset, or both a slope and an intercept of a centraltendency of in vitro sensitivity of the first subset.

In some embodiments, determining individualized calibration informationfor each analyte sensor in the second subset includes performing (a)-(c)independently for each analyte sensor in the second subset usingprocessing circuitry: (a) determining an in vitro sensitivity of arespective analyte sensor in the second subset using at least therepresentation of the individualized manufacturing parameter for therespective analyte sensor and the representation of the in vitrosensitivity of the first subset; (b) determining an in vivo sensitivityof the respective analyte sensor using a representation of the in vitrosensitivity of the respective analyte sensor; and (c) determiningindividualized calibration information for the respective analyte sensorthat corresponds to the in vivo sensitivity of the respective analytesensor. In certain embodiments, determining the in vitro sensitivity ofthe respective analyte sensor in the second subset includes modeling acorrelation between the representation of the individualizedmanufacturing parameter for the respective analyte sensor and therepresentation of the in vitro sensitivity of the first subset, wheremodeling the correlation utilizes one of the following models: a linearregression model; a multiple variable regression model; a random forestmodel; a non-linear model; a Bayesian regression model; a neuralnetwork; a machine learning model; a non-random decision tree; or adiscriminant analysis model. In certain embodiments, modeling thecorrelation utilizes a model at least partially represented by:SC_(MD)=SC_(B)+α+(βRMP_(A)) or SC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A)))),where SC_(MD) is the in vitro sensitivity of the respective analytesensor, SC_(B) is the representation of the in vitro sensitivity of thefirst subset, α is a zero or non-zero adjustment factor, RMP_(A) is therepresentation of the individualized manufacturing parameter for therespective analyte sensor, and β is a coefficient for RMP_(A). Incertain embodiments, modeling the correlation utilizes a model at leastpartially represented by: SC_(MD)=SC_(B)+α+(βRMP_(A))+(δ RMP_(A) ²) orSC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A)) (δ RMP_(A) ²))), where SC_(MD) is thein vitro sensitivity of the respective analyte sensor, SC_(B) is therepresentation of the in vitro sensitivity of the first subset, α is azero or non-zero adjustment factor, RMP_(A) is the representation of theindividualized manufacturing parameter for the respective analytesensor, and β is a coefficient for RMP_(A), and δ is a coefficient forRMP_(A) squared.

In some embodiments, the individualized manufacturing parameter is afirst individualized manufacturing parameter, and determiningindividualized calibration information for each analyte sensor in thesecond subset includes performing (a)-(c) independently for each analytesensor in the second subset using processing circuitry: (a) determiningan in vitro sensitivity of a respective analyte sensor in the secondsubset using at least: the representation of the first individualizedmanufacturing parameter for the respective analyte sensor, arepresentation of a second individualized manufacturing parameter forthe respective analyte sensor, and the representation of the in vitrosensitivity of the first subset; (b) determining an in vivo sensitivityof the respective analyte sensor using a representation of the in vitrosensitivity of the respective analyte sensor; and (c) determiningindividualized calibration information for the respective analyte sensorthat corresponds to the in vivo sensitivity of the respective analytesensor. In certain embodiments, the representation of the firstindividualized manufacturing parameter for the respective analytesensor, the representation of a second individualized manufacturingparameter for the respective analyte sensor, and the representation ofthe in vitro sensitivity of the first subset are input into a model todetermine the in vitro sensitivity of the respective analyte sensor. Incertain embodiments, the model is at least partially represented by:SC_(MD)=SC_(B)+α+(βRMP_(A))+(δRMP_(A) ²)+(γRMP_(B))+(εRMP_(B))+(ρRMP_(A) RMP_(B)) or SC_(MD)=SC_(B)+(1+0.01(α+(βRMP_(A) ²)+(δ RMP_(B)+(γRMP_(B))+(εRMP_(B) ²)+(ρRMP_(A) RMP_(B)))),where SC_(MD) is the in vitro sensitivity of the respective analytesensor, SC_(B) is the representation of the in vitro sensitivity of thefirst subset, α is a zero or non-zero adjustment factor, RMP_(A) is therepresentation of the first individualized manufacturing parameter forthe respective analyte sensor, β is a coefficient for RMP_(A), δ is acoefficient for RMP_(A) squared, RMP_(B) is the second individualizedmanufacturing parameter, γ is a coefficient for RMP_(B), ε is acoefficient for RMP_(B) squared, and ρ is a coefficient for the productof RMP_(A) and RMP_(B).

In some embodiments, each analyte sensor of the multitude includes asensing region and a membrane for the sensing region, where measuring anindividualized manufacturing parameter of each analyte sensor in themultitude includes measuring a size of the sensing region and a size ofthe membrane of each analyte sensor in the multitude, and wheredetermining the in vitro sensitivity of the respective analyte sensor inthe second subset includes inputting a representation of the size of thesensing region, a representation of the size of the membrane, and arepresentation of the in vitro sensitivity into a model.

In some embodiments, the in vivo sensitivity of the respective analytesensor is determined by applying a representation of the in vitrosensitivity of the respective analyte sensor to a transfer function. Insome embodiments, determining individualized calibration information forthe respective analyte sensor includes identifying, from a multitude ofpredetermined calibration codes, a calibration code that most closelyrepresents the in vivo sensitivity of the respective analyte sensor.

In some embodiments, each analyte sensor in the second subset isassociated with a different sensor electronics assembly of a multitudeof sensor electronics assemblies, and each sensor electronics assemblyof the multitude of sensor electronics assemblies includes anon-transitory memory. In certain embodiments, the non-transitory memoryof each sensor electronics assembly has individualized calibrationinformation for the associated analyte sensor stored thereon. In certainembodiments, each sensor electronics assembly in the multitude of sensorelectronics assemblies includes processing circuitry communicativelycoupled with the non-transitory memory. In some embodiments, eachnon-transitory memory includes instructions that, when executed by theprocessing circuitry communicatively coupled thereto, causes thatprocessing circuitry to determine an analyte level from raw analyte datameasured by the associated analyte sensor and from the individualizedcalibration information for that associated analyte sensor. In otherembodiments, each non-transitory memory includes instructions that, whenexecuted by the processing circuitry communicatively coupled thereto,causes that processing circuitry to cause transmission of theindividualized calibration information for the associated analyte sensorto a wirelessly connected reader device.

In some embodiments, determining individualized calibration informationfor each analyte sensor in the second subset includes performing (a) and(b) independently for each analyte sensor in the second subset usingprocessing circuitry: (a) determining an in vitro sensitivity of arespective analyte sensor in the second subset using at least therepresentation of the individualized manufacturing parameter for therespective analyte sensor and the representation of the in vitrosensitivity of the first subset; and (b) determining individualizedcalibration information for the respective analyte sensor thatcorresponds to the in vitro sensitivity of the respective analytesensor.

In some embodiments, determining individualized calibration informationfor each analyte sensor in the second subset includes performing (a) and(b) independently for each analyte sensor in the second subset usingprocessing circuitry: (a) determining a first in vitro sensitivity of arespective analyte sensor in the second subset using at least therepresentation of the individualized manufacturing parameter for therespective analyte sensor and the representation of the in vitrosensitivity of the first subset; (b) determining a second in vitrosensitivity of the respective analyte sensor in the second subset usingat least a representation of the first in vitro sensitivity of therespective analyte sensor; and (c) determining individualizedcalibration information for the respective analyte sensor thatcorresponds to the in vitro sensitivity of the respective analytesensor. In certain embodiments, the first in vitro sensitivitycorresponds to the presence of the analyte in an analyte test solution,and the second in vitro sensitivity corresponds to the presence of theanalyte in a bodily fluid.

In some embodiments, each medical device in the multitude is an in vitroanalyte sensor, optionally a test strip. In certain embodiments, each invitro analyte sensor includes a working pad and the individualizedmanufacturing parameter is a size of the working pad. In certainembodiments, the individualized manufacturing parameter is an area ofthe working pad, while in other embodiments the individualizedmanufacturing parameter is a thickness of the working pad. In certainembodiments, each in vitro analyte sensor includes at least oneelectrical trace and the individualized manufacturing parameter is aresistance of the trace.

In some embodiments, the individualized manufacturing parameter of eachmedical device in the multitude is measured during or after a stage ofmanufacturing of the multitude of medical devices.

In some embodiments, the method further includes assigning theindividualized calibration information to each medical device in thesecond subset.

In many embodiments, the biochemical attribute is a level of glucose.

In some embodiments, the first and second subsets are taken from a sameproduction lot. In some embodiments, the multitude of medical devices isa production lot of the medical devices.

In some embodiments, the plurality of medical devices is a plurality ofanalyte sensors each including a sensor substrate, and at leastpartially manufacturing the plurality of analyte sensors includes:modifying an area of a surface of each sensor substrate withelectromagnetic radiation to create a modified area; and applying aliquid agent to the surface of each sensor substrate such that theliquid agent comes to rest in a target area on the surface, where thetarget area is determined at least in part by the location of themodified area. The modified area can border the target area, and themodified area can repel or attract the liquid agent. In someembodiments, at least partially manufacturing the plurality of analytesensors can further include: focusing a laser on the surface of eachsensor substrate; and activating the laser to modify the area of thesurface of each sensor substrate with electromagnetic radiation tocreate the modified area. In some embodiments, at least partiallymanufacturing the plurality of analyte sensors can further include:transferring each sensor substrate to a liquid agent dispense systemhaving a nozzle; and applying the liquid agent from the nozzle to thesurface of each sensor substrate such that the liquid agent comes torest in the target area on the surface.

In some embodiments, the plurality of medical devices is a plurality ofanalyte sensors each including a sensor substrate, and at leastpartially manufacturing the plurality of analyte sensors includes:creating a well in each sensor substrate; and applying a liquid agentinto the well in each sensor substrate such that the liquid agent comesto rest in the well. The liquid agent can cover at least a portion ofthe bottom and substantially contact the sidewall. The method canfurther include: aligning a tip of a tool with an alignment feature on asurface of the sensor substrate; and forcing the tip of the tool intothe substrate to create the well in the substrate. The method canfurther include: transferring the substrate to a liquid agent dispensesystem having a nozzle, where applying the liquid agent into the well inthe sensor substrate such that the liquid agent comes to rest in thewell includes dispensing a drop of the liquid agent from the nozzle intothe well.

In many embodiments, a method for calibrating individual medical devicesis provided, where the method includes: measuring an individualizedmanufacturing parameter of each medical device in a multitude of medicaldevices; and determining, with processing circuitry, individualizedcalibration information for each medical device in the multitude usingat least a representation of the individualized manufacturing parameterfor each medical device and a representation of a baseline sensingcharacteristic.

In some embodiments, each of the medical devices in the multitude is ananalyte sensor adapted to sense an analyte.

In some embodiments, the multitude of medical devices is a secondmultitude, and the method further includes determining the baselinesensing characteristic from clinical test data of a first multitude ofmedical devices.

In some embodiments, the multitude of medical devices is a secondmultitude, and the method further includes: measuring an individualizedmanufacturing parameter of each medical device in a first multitude ofmedical devices; performing clinical testing with the first multitude ofmedical devices to obtain clinical test data; and determining thebaseline sensing characteristic from the clinical test data. In certainembodiments, each medical device in the first multitude is an in vivoanalyte sensor, and the clinical testing is in vivo testing. In certainembodiments, each medical device in the first multitude is an in vitroanalyte sensor, and the clinical testing is in vitro testing. In certainembodiments, the second multitude is a production lot of medicaldevices. In certain embodiments, the first and second pluralities ofmedical devices are from different production lots.

In some embodiments, determining individualized calibration informationfor each sensor in the multitude includes performing (a) and (b)independently for each sensor in the multitude using processingcircuitry: (a) determining a representation of an individualized sensingcharacteristic of a respective analyte sensor in the multitude using atleast the representation of the individualized manufacturing parameterfor the respective sensor and the representation of the baseline sensingcharacteristic; and (b) determining individualized calibrationinformation for the respective analyte sensor that corresponds to theindividualized sensing characteristic of the respective analyte sensor.In certain embodiments, determining the representation of theindividualized sensing characteristic of the respective analyte sensorincludes modeling a correlation between the representation of theindividualized manufacturing parameter for the respective analyte sensorand the representation of the baseline sensing characteristic. Incertain embodiments, modeling the correlation utilizes at least one ofthe following: a linear regression model; a multiple variable regressionmodel; a random forest model; a non-linear model; a Bayesian regressionmodel; a neural network; a machine learning model; a non-random decisiontree; or a discriminant analysis model. In certain embodiments, modelingthe correlation utilizes a model at least partially represented by:SC_(MD)=SC_(B)+α+(βRMP_(A)) or SC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A)))),where SC_(MD) is the representation of the individualized sensingcharacteristic of the respective analyte sensor, SC_(B) is therepresentation of the baseline sensing characteristic, α is a zero ornon-zero adjustment factor, RMP_(A) is the representation of theindividualized manufacturing parameter for the respective analytesensor, and β is a coefficient for RMP_(A). In certain embodiments,modeling the correlation utilizes a model at least partially representedby: SC_(MD)=SC_(B)+α+(βRMP_(A))+(δ RMP_(A) ²) orSC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A))+(δ RMP_(A) ²))), where SC_(MD) is therepresentation of the individualized sensing characteristic of therespective analyte sensor, SC_(B) is the representation of the baselinesensing characteristic, α is a zero or non-zero adjustment factor,RMP_(A) is the representation of the individualized manufacturingparameter for the respective analyte sensor, β is a coefficient forRMP_(A), and δ is a coefficient for RMP_(A) squared.

In some embodiments, the individualized manufacturing parameter is afirst individualized manufacturing parameter, and the method furtherincludes measuring a second individualized manufacturing parameter ofeach medical device in the multitude of medical devices. In certainembodiments, determining individualized calibration information for eachanalyte sensor in the multitude includes performing (a)-(b)independently for each analyte sensor in the multitude using processingcircuitry: (a) determining an individualized sensing characteristic of arespective analyte sensor in the multitude using at least: therepresentation of the first individualized manufacturing parameter forthe respective analyte sensor, a representation of the secondindividualized manufacturing parameter for the respective analytesensor, and the representation of the baseline sensing characteristic;and (b) determining individualized calibration information for therespective analyte sensor that corresponds to the individualized sensingcharacteristic of the respective analyte sensor. In certain embodiments,the method further includes modeling a correlation between therepresentation of the first individualized manufacturing parameter forthe respective analyte sensor, the representation of a secondindividualized manufacturing parameter for the respective analytesensor, and the representation of the baseline sensing characteristic todetermine the individualized sensing characteristic of the respectiveanalyte sensor. In certain embodiments, modeling the correlationutilizes a model at least partially represented by:SC_(MD)=SC_(B)+α+(βRMP_(A))+(δRMP_(A) ²)+(γRMP_(B))+(εRMP_(B))+(ρRMP_(A)RMP_(B)) or SC_(MD)=SC_(B)+(1+0.01 (α+(βRMP_(A))+(δRMP_(A)²)+(γRMP_(B))+(εRMP_(B) ²)+(ρRMP_(A) RMP_(B)))), where SC_(MD) is arepresentation of the individualized sensing characteristic of therespective analyte sensor, SC_(B) is the representation of the baselinesensing characteristic, α is a zero or non-zero adjustment factor,RMP_(A) is the representation of the first individualized manufacturingparameter for the respective analyte sensor, β is a coefficient forRMP_(A), δ is a coefficient for RMP_(A) squared, RMP_(B) is the secondindividualized manufacturing parameter, γ is a coefficient for RMP_(B),ε is a coefficient for RMP_(B) squared, and ρ is a coefficient for theproduct of RMP_(A) and RMP_(B).

In some embodiments, the individualized manufacturing parameter is asize of a sensing region of each medical device or a size of a membraneof each medical device. In some embodiments, the multitude of medicaldevices is a production lot of the medical devices.

In some embodiments, the individualized manufacturing parameter is asize of a sensing region of each medical device, the sensing regionincluding a sensing element, where the sensing element is in a well of asensor substrate and/or the sensing element is on or adjacent to amodified area of the sensor substrate having a liquid mobilitycharacteristic different than an adjacent area of the sensor substrate.

In many embodiments, a method for calibrating individual analyte sensorsis provided, where the method includes: at least partially manufacturinga multitude of analyte sensors, the multitude including a first subsetand a second subset, where each of the analyte sensors in the multitudeare adapted for in vivo sensing of an analyte level; measuring anindividualized manufacturing parameter of each analyte sensor in themultitude; determining, with processing circuitry, an in vitrosensitivity of the first subset from data obtained by in vitro testingthe first subset; and performing (a)-(c) for each analyte sensor in thesecond subset using processing circuitry: (a) determining an in vitrosensitivity of a respective analyte sensor in the second subset using atleast the representation of the individualized manufacturing parameterfor the respective analyte sensor and the representation of the in vitrosensitivity of the first subset; (b) determining an in vivo sensitivityof the respective analyte sensor using a representation of the in vitrosensitivity of the respective analyte sensor; and (c) determiningindividualized calibration information for the respective analyte sensorthat corresponds to the in vivo sensitivity of the respective analytesensor.

In some embodiments, each analyte sensor in the multitude includes asensing region and the individualized manufacturing parameter is a sizeof the sensing region. In certain embodiments, the representation of theindividualized manufacturing parameter for the respective analyte sensoris a deviation of the size of the sensing region of the respectiveanalyte sensor from a central tendency of a size of the sensing regionfor the multitude of analyte sensors.

In some embodiments, the sensing region includes a sensing element, thesensing element being in a well of a sensor substrate and/or the sensingelement being on or adjacent to a modified area of the sensor substratehaving a liquid mobility characteristic different than an adjacent areaof the sensor substrate.

In some embodiments, each of the analyte sensors in the multitudeincludes a membrane for the sensing region and the individualizedmanufacturing parameter is a size of the membrane. In certainembodiments, the representation of the individualized manufacturingparameter for the respective analyte sensor is a deviation of the sizeof the membrane of the respective analyte sensor from a central tendencyof a size of the membrane for the multitude of analyte sensors.

In some embodiments, each of the analyte sensors in the multitudeincludes a sensing region and a membrane for the sensing region, wheremeasuring an individualized manufacturing parameter of each analytesensor in the multitude includes measuring a size of the sensing regionand a size of the membrane of each analyte sensor. In certainembodiments, the in vitro sensitivity of the respective analyte sensoris determined using: a representation of the size of the sensing regionof the respective analyte sensor; a representation of the size of themembrane of the respective analyte sensor; and a representation of thein vitro sensitivity of the first subset. In certain embodiments, therepresentation of the in vitro sensitivity includes a slope of a centraltendency of in vitro sensitivity of the first subset, or an intercept ofa central tendency of in vitro sensitivity of the first subset, or aslope and an intercept of a central tendency of in vitro sensitivity ofthe first subset. In certain embodiments, the in vitro sensitivity ofthe respective analyte sensor in the second subset is determined bymodeling a correlation between a representation of the size of thesensing region of the respective analyte sensor, a representation of thesize of the membrane of the respective analyte sensor, and arepresentation of the in vitro sensitivity of the first subset. Incertain embodiments, modeling the correlation utilizes at least one ofthe following: a linear regression model; a multiple variable regressionmodel; a random forest model; a non-linear model; a Bayesian regressionmodel; a neural network; a machine learning model; a non-random decisiontree; or a discriminant analysis model.

In some embodiments, the in vivo sensitivity of the respective analytesensor is determined by applying a representation of the in vitrosensitivity of the respective analyte sensor to a transfer function.

In some embodiments, determining individualized calibration informationfor the respective analyte sensor includes identifying, from a multitudeof predetermined calibration codes, a calibration code that most closelyrepresents the in vivo sensitivity of the respective analyte sensor.

In some embodiments, each analyte sensor in the second subset isassociated with a different sensor electronics assembly of a multitudeof sensor electronics assemblies, each sensor electronics assembly ofthe multitude of sensor electronics assemblies including anon-transitory memory. In certain embodiments, the non-transitory memoryof each sensor electronics assembly has individualized calibrationinformation for the associated analyte sensor stored thereon. In certainembodiments, each sensor electronics assembly in the multitude of sensorelectronics assemblies includes processing circuitry communicativelycoupled with the non-transitory memory. In certain embodiments, eachnon-transitory memory includes instructions that, when executed by theprocessing circuitry communicatively coupled thereto, causes thatprocessing circuitry to determine an analyte level from raw analyte datameasured by the associated analyte sensor and from the individualizedcalibration information for that associated analyte sensor. In certainembodiments, each non-transitory memory includes instructions that, whenexecuted by the processing circuitry communicatively coupled thereto,causes that processing circuitry to cause transmission of theindividualized calibration information for the associated analyte sensorto a wirelessly connected reader device.

In some embodiments, the analyte level is a glucose level.

In some embodiments, the first and second subsets are taken from a sameproduction lot. In some embodiments, the multitude of in vivo analytesensors is a production lot of the analyte sensors.

In some embodiments, the in vitro testing includes applying an analytesolution to each of the analyte sensors in the first subset. In someembodiments, the in vitro testing degrades or contaminates each analytesensor in the first subset.

In many embodiments, a method for calibrating individual medical devicesis provided, where the method includes: at least partially manufacturinga first medical device and a second medical device, where the first andsecond medical devices are adapted to sense a biochemical attribute;measuring a manufacturing parameter of the second medical device;determining, with processing circuitry, an in vitro sensingcharacteristic of the first medical device from data obtained by invitro testing the first medical device; and determining, with processingcircuitry, calibration information for the second medical device usingat least a representation of the manufacturing parameter of the secondmedical device and a representation of the in vitro sensingcharacteristic of the first medical device.

In some embodiments, measuring the manufacturing parameter of the secondmedical device is performed by a manufacturer.

In some embodiments, the first medical device is a first analyte sensor,the second medical device is a second analyte sensor, and thebiochemical attribute is an analyte level. In certain embodiments, thefirst and second analyte sensors are adapted to sense the analyte levelin vivo. In certain embodiments, the second analyte sensor includes asensing region and a membrane for the sensing region and in certainembodiments, the manufacturing parameter is a size of the sensing regionor a size of the membrane. In certain embodiments, measuring themanufacturing parameter of the second analyte sensor includes measuringa size of the sensing region and a size of the membrane of the secondanalyte sensor, and the calibration information for the second analytesensor is determined using a representation of the size of the sensingregion, a representation of the size of the membrane, and arepresentation of the in vitro sensing characteristic of the firstanalyte sensor.

In some embodiments, the sensing region includes a sensing element, thesensing element being in a well of a sensor substrate and/or the sensingelement being on or adjacent to a modified area of the sensor substratehaving a liquid mobility characteristic different than an adjacent areaof the sensor substrate.

In some embodiments, the in vitro sensing characteristic is a slope of asensitivity of the first analyte sensor to the analyte level. In certainembodiments, the in vitro sensing characteristic is the sensitivity ofthe first analyte sensor to the analyte level.

In some embodiments, determining calibration information for the secondanalyte sensor includes: determining, with processing circuitry, an invitro sensing characteristic of the second analyte sensor using at leastthe representation of the manufacturing parameter of the second analytesensor and the representation of the in vitro sensing characteristic ofthe first analyte sensor; determining, with processing circuitry, an invivo sensing characteristic of the second analyte sensor using arepresentation of the in vitro sensing characteristic of the secondanalyte sensor; and determining, with processing circuitry, calibrationinformation for the second analyte sensor that corresponds to the invivo sensing characteristic of the second analyte sensor. In certainembodiments, the method further includes determining the in vitrosensing characteristic of the second analyte sensor with a model, wherethe representation of the manufacturing parameter of the second analytesensor and the representation of the in vitro sensing characteristic ofthe first analyte sensor are inputs to the model. In certainembodiments, the model is one of the following: a linear regressionmodel; a multiple variable regression model; a random forest model; anon-linear model; a Bayesian regression model; a neural network; amachine learning model; a non-random decision tree; or a discriminantanalysis model.

In certain embodiments, the second analyte sensor includes a sensingregion and the manufacturing parameter is a size of the sensing region.In certain embodiments, the second analyte sensor includes a membraneand the manufacturing parameter is a size of the membrane. In certainembodiments, the second analyte sensor includes a sensing region and amembrane for the sensing region, where measuring the manufacturingparameter of the second analyte sensor includes measuring a size of thesensing region and a size of the membrane of the second analyte sensor,and where a representation of the size of the sensing region, arepresentation of the size of the membrane, and a representation of thein vitro sensing characteristic are inputs to the model.

In certain embodiments, the in vivo sensing characteristic of the secondanalyte sensor is determined by applying a representation of the invitro sensing characteristic of the second analyte sensor to a transferfunction.

In certain embodiments, determining calibration information for thesecond analyte sensor that corresponds to the in vivo sensingcharacteristic of the second analyte sensor includes identifying, from amultitude of predetermined calibration codes, a calibration code thatmost closely represents the in vivo sensing characteristic of the secondanalyte sensor.

In some embodiments, the method further includes storing the calibrationinformation for the second analyte sensor in a non-transitory memory ofsensor electronics assigned to the second analyte sensor. In certainembodiments, the sensor electronics include processing circuitry and thenon-transitory memory includes instructions that, when executed by theprocessing circuitry, cause the processing circuitry to determine ananalyte level from a raw analyte measurement made by the second analytesensor and the calibration information for the second analyte sensor. Incertain embodiments, the sensor electronics include processing circuitryand the non-transitory memory includes instructions that, when executedby the processing circuitry, cause the processing circuitry to causetransmission of the calibration information for the second analytesensor to a wirelessly connected reader device.

In some embodiments, the method further includes storing the calibrationinformation for the second analyte sensor in a non-transitory memory ofa server. In certain embodiments, the method further includes: receivinga request, at the server, for the calibration information for the secondanalyte sensor from a requesting device; and downloading the calibrationinformation from the server to the requesting device.

In some embodiments, the method includes: at least partiallymanufacturing a third medical device capable of sensing a biochemicalattribute; measuring a manufacturing parameter of the third medicaldevice; and determining, with processing circuitry, calibrationinformation for the third medical device using a representation of themanufacturing parameter of the third medical device and therepresentation of the in vitro sensing characteristic of the firstmedical device.

In some embodiments, the second medical device is not in vitro tested.

In many embodiments, a method for calibrating individual medical devicesadapted to sense a biochemical attribute is provided, where the methodincludes: determining, with processing circuitry, a sensingcharacteristic of a first medical device; and determining, withprocessing circuitry, calibration information for a second medicaldevice using at least a representation of a manufacturing parameter ofthe second medical device and a representation of the sensingcharacteristic of the first medical device.

In some embodiments, the method further includes at least partiallymanufacturing the first medical device and the second medical device andmeasuring the manufacturing parameter of the second medical device.

In some embodiments, the sensing characteristic is an in vitro sensingcharacteristic determined from data obtained by in vitro testing thefirst medical device.

In some embodiments, the first medical device is a first analyte sensor,the second medical device is a second analyte sensor, and thebiochemical attribute is an analyte level. In certain embodiments, thefirst and second analyte sensors are adapted to sense the analyte levelin vivo.

In some embodiments, the second medical device includes a sensingregion. In certain embodiments, the manufacturing parameter is a size ofthe sensing region.

In some embodiments, the second medical device includes a membrane. Incertain embodiments, the manufacturing parameter is a size of themembrane.

In some embodiments, the first and second medical devices are in vitroanalyte sensors. In certain embodiments, each in vitro analyte sensor isa test strip. In certain embodiments, each in vitro analyte sensorincludes a working pad and the manufacturing parameter is a size of theworking pad, an area of the working pad, or a thickness of the workingpad. In certain embodiments, each in vitro analyte sensor includes anelectrical trace and the manufacturing parameter is a resistance of theelectrical trace.

In some embodiments, the manufacturing parameter is a qualitative value.

In some embodiments, the sensing region includes a sensing element, thesensing element being in a well of a sensor substrate and/or the sensingelement being on or adjacent to a modified area of the sensor substratehaving a liquid mobility characteristic different than an adjacent areaof the sensor substrate.

In many embodiments, a computer system for calibrating individualmedical devices adapted to sense a biochemical attribute is provided,where the computer system includes: processing circuitry andnon-transitory memory communicatively coupled with the processingcircuitry, where the non-transitory memory has a multitude ofinstructions stored thereon that, when executed by the processingcircuitry, cause the processing circuitry to: determine a sensingcharacteristic of a first medical device; and determine calibrationinformation for a second medical device using at least a representationof a manufacturing parameter of the second medical device and arepresentation of the sensing characteristic of the first medicaldevice.

In some embodiments, the sensing characteristic is an in vitro sensingcharacteristic, where the multitude of instructions, when executed bythe processing circuitry, cause the processing circuitry to determinethe in vitro sensing characteristic from in vitro test data of the firstmedical device.

In some embodiments, the first medical device is a first analyte sensor,the second medical device is a second analyte sensor, and thebiochemical attribute is an analyte level. In certain embodiments, thefirst and second analyte sensors are adapted to sense the analyte levelin vivo. In certain embodiments, the manufacturing parameter is a sizeof a sensing region of the second analyte sensor. In certainembodiments, the manufacturing parameter is a size of a membrane of thesecond analyte sensor.

In some embodiments, the sensing region includes a sensing element, thesensing element being in a well of a sensor substrate and/or the sensingelement being on or adjacent to a modified area of the sensor substratehaving a liquid mobility characteristic different than an adjacent areaof the sensor substrate.

In some embodiments, the first medical device is a first in vitroanalyte sensor and the second medical device is a second in vitroanalyte sensor. In certain embodiments, each in vitro analyte sensor isa strip. In certain embodiments, each in vitro analyte sensor includes aworking pad and the manufacturing parameter is a size of the workingpad, an area of the working pad, or a thickness of the working pad. Incertain embodiments, each in vitro analyte sensor includes an electricaltrace and the manufacturing parameter is a resistance of the electricaltrace.

In some embodiments, the manufacturing parameter is a qualitative value.In some embodiments, the manufacturing parameter is an individualizedmanufacturing parameter that is quantitative.

In many embodiments, a computer system for calibrating individualmedical devices adapted to sense a biochemical attribute is provided,where the computer system includes: processing circuitry andnon-transitory memory communicatively coupled with the processingcircuitry, where the non-transitory memory has a multitude ofinstructions stored thereon that, when executed by the processingcircuitry, cause the processing circuitry to: determine an in vitrosensing characteristic of a first subset of a multitude of medicaldevices from in vitro test data of the first subset; and determineindividualized calibration information for each medical device in asecond subset of the multitude of medical devices using at least arepresentation of an individualized manufacturing parameter for eachmedical device in the second subset and a representation of the in vitrosensing characteristic of the first subset, where the medical devices inthe first subset are different from the medical devices in the secondsubset.

In some embodiments, each of the medical devices in the multitude is ananalyte sensor and the biochemical attribute is a level of an analyte.In certain embodiments, each analyte sensor in the multitude is adaptedto sense the analyte level in vivo, and the in vitro sensingcharacteristic is in vitro sensitivity to the analyte.

In some embodiments, the individualized manufacturing parameter is asize of a sensing region of each analyte sensor in the second subset. Incertain embodiments, the size of the sensing region is representative ofat least one of the following: a width of the sensing region, a lengthof the sensing region, a thickness of the sensing region, a peripherallength of the sensing region, an area of the sensing region, or a volumeof the sensing region.

In some embodiments, the representation of the individualizedmanufacturing parameter for a respective analyte sensor in the secondsubset is a deviation of the size of a sensing region of the respectiveanalyte sensor from a central tendency of a size of a sensing region forthe multitude of analyte sensors.

In some embodiments, the sensing region includes a sensing element, thesensing element being in a well of a sensor substrate and/or the sensingelement being on or adjacent to a modified area of the sensor substratehaving a liquid mobility characteristic different than an adjacent areaof the sensor substrate.

In some embodiments, the individualized manufacturing parameter is asize of a membrane of each analyte sensor in the second subset. Incertain embodiments, the size of the membrane is representative of atleast one of the following: a width of the membrane, a length of themembrane, a thickness of the membrane, a peripheral length of themembrane, an area of the membrane, or a volume of the membrane. Incertain embodiments, the representation of the individualizedmanufacturing parameter for a respective analyte sensor in the secondsubset is a deviation of the size of the membrane of the respectiveanalyte sensor from a central tendency of a size of the membrane for themultitude of analyte sensors.

In some embodiments, the multitude of instructions, when executed by theprocessing circuitry, cause the processing circuitry to determine theindividualized calibration information for each analyte sensor in thesecond subset using: a representation of a size of a sensing region of arespective analyte sensor in the second subset; a representation of asize of a membrane of the respective analyte sensor in the secondsubset; and the representation of the in vitro sensitivity of the firstsubset. In certain embodiments, the representation of the in vitrosensitivity includes a slope of a central tendency of in vitrosensitivity of the first subset, or an intercept of a central tendencyof in vitro sensitivity of the first subset, or a slope and an interceptof a central tendency of in vitro sensitivity of the first subset.

In some embodiments, the multitude of instructions, when executed by theprocessing circuitry, cause the processing circuitry to determineindividualized calibration information for each analyte sensor in thesecond subset by performance of (a)-(c) independently for each analytesensor in the second subset: (a) determine an in vitro sensitivity of arespective analyte sensor in the second subset with at least therepresentation of the individualized manufacturing parameter for therespective analyte sensor and the representation of the in vitrosensitivity of the first subset; (b) determine an in vivo sensitivity ofthe respective analyte sensor with a representation of the in vitrosensitivity of the respective analyte sensor; and (c) determineindividualized calibration information for the respective analyte sensorthat corresponds to the in vivo sensitivity of the respective analytesensor. In certain embodiments, the multitude of instructions, whenexecuted by the processing circuitry, cause the processing circuitry todetermine the in vitro sensitivity of the respective analyte sensor inthe second subset by modeling a correlation between the representationof the individualized manufacturing parameter for the respective analytesensor and the representation of the in vitro sensitivity of the firstsubset with a model. In certain embodiments, the model is one of thefollowing: a linear regression model; a multiple variable regressionmodel; a random forest model; a non-linear model; a Bayesian regressionmodel; a neural network; a machine learning model; a non-random decisiontree; or a discriminant analysis model. In certain embodiments, themodel is at least partially represented by: SC_(MD)=SC_(B)+α+(β RMP_(A))or SC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A)))), where SC_(MD) is the in vitrosensitivity of the respective analyte sensor, SC_(B) is therepresentation of the in vitro sensitivity of the first subset, α is azero or non-zero adjustment factor, RMP_(A) is the representation of theindividualized manufacturing parameter for the respective analytesensor, and β is a coefficient for RMP_(A). In certain embodiments, themodel is at least partially represented by:SC_(MD)=SC_(B)+α+(βRMP_(A))+(δ RMP_(A) ²) orSC_(MD)=SC_(B)+(1+0.1(α+(βRMP_(A))+(δ RMP_(A) ²))), where SC_(MD) is thein vitro sensitivity of the respective analyte sensor, SC_(B) is therepresentation of the in vitro sensitivity of the first subset, α is azero or non-zero adjustment factor, RMP_(A) is the representation of theindividualized manufacturing parameter for the respective analytesensor, and β is a coefficient for RMP_(A), and δ is a coefficient forRMP_(A) squared.

In some embodiments, the individualized manufacturing parameter is afirst individualized manufacturing parameter, and the multitude ofinstructions, when executed by the processing circuitry, cause theprocessing circuitry to determine individualized calibration informationfor each analyte sensor in the second subset by performance of (a)-(c)independently for each analyte sensor in the second subset: (a)determine an in vitro sensitivity of a respective analyte sensor in thesecond subset using at least: the representation of the firstindividualized manufacturing parameter for the respective analytesensor, a representation of a second individualized manufacturingparameter for the respective analyte sensor, and the representation ofthe in vitro sensitivity of the first subset; (b) determine an in vivosensitivity of the respective analyte sensor using a representation ofthe in vitro sensitivity of the respective analyte sensor; and (c)determine individualized calibration information for the respectiveanalyte sensor that corresponds to the in vivo sensitivity of therespective analyte sensor. In certain embodiments, the representation ofthe first individualized manufacturing parameter for the respectiveanalyte sensor, the representation of a second individualizedmanufacturing parameter for the respective analyte sensor, and therepresentation of the in vitro sensitivity of the first subset are inputinto a model to determine the in vitro sensitivity of the respectiveanalyte sensor. In certain embodiments, the model is at least partiallyrepresented by: SC_(MD)=SC_(B)+α+(βRMP_(A))+(δRMP_(A)²)+(γRMP_(B))+(εRMP_(B) ²)+(ρRMP_(A) RMP_(B)) or SC_(MD)=SC_(B)+(1+0.01(α+(βRMP_(A))+(δRMP_(A) ²)+(γRMP_(B))+(εRMP_(B) ²)+(ρRMP_(A) RMP_(B)))),where SC_(MD) is the in vitro sensitivity of the respective analytesensor, SC_(B) is the representation of the in vitro sensitivity of thefirst subset, α is a zero or non-zero adjustment factor, RMP_(A) is therepresentation of the first individualized manufacturing parameter forthe respective analyte sensor, β is a coefficient for RMP_(A), δ is acoefficient for RMP_(A) squared, RMP_(B) is the second individualizedmanufacturing parameter, γ is a coefficient for RMP_(B), ε is acoefficient for RMP_(B) squared, and ρ is a coefficient for the productof RMP_(A) and RMP_(B).

In some embodiments, each analyte sensor of the multitude includes asensing region and the individualized manufacturing parameter is a sizeof the sensing region.

In some embodiments, each analyte sensor of the multitude includes amembrane and the individualized manufacturing parameter is a size of themembrane.

In some embodiments, each analyte sensor of the multitude includes asensing region and a membrane for the sensing region, where themultitude of instructions, when executed by the processing circuitry,cause the processing circuitry to determine the in vitro sensitivity ofthe respective analyte sensor in the second subset by input of arepresentation of a size of the sensing region of the respective analytesensor, a representation of a size of the membrane of the respectiveanalyte sensor, and a representation of the in vitro sensitivity into amodel.

In some embodiments, the multitude of instructions, when executed by theprocessing circuitry, cause the processing circuitry to determine the invivo sensitivity of the respective analyte sensor by application of arepresentation of the in vitro sensitivity of the respective analytesensor to a transfer function.

In some embodiments, the multitude of instructions, when executed by theprocessing circuitry, cause the processing circuitry to determineindividualized calibration information for the respective analyte sensorby identification of, from a multitude of predetermined calibrationcodes, a calibration code that most closely represents the in vivosensitivity of the respective analyte sensor.

In some embodiments, each analyte sensor in the second subset isassociated with a different sensor electronics assembly of a multitudeof sensor electronics assemblies, and each sensor electronics assemblyof the multitude of sensor electronics assemblies includes anon-transitory memory, and the multitude of instructions, when executedby the processing circuitry, cause the processing circuitry to outputcorresponding individualized calibration information for storage in eachnon-transitory memory.

In some embodiments, the multitude of instructions, when executed by theprocessing circuitry, cause the processing circuitry to determineindividualized calibration information for each analyte sensor in thesecond subset by performance of (a) and (b) independently for eachanalyte sensor in the second subset: (a) determine an in vitrosensitivity of a respective analyte sensor in the second subset with atleast the representation of the individualized manufacturing parameterfor the respective analyte sensor and the representation of the in vitrosensitivity of the first subset; and (b) determine individualizedcalibration information for the respective analyte sensor thatcorresponds to the in vitro sensitivity of the respective analytesensor.

In some embodiments, each medical device in the multitude is an in vitroanalyte sensor. In certain embodiments, each in vitro analyte sensor isa test strip. In certain embodiments, each in vitro analyte sensorincludes a working pad and the manufacturing parameter is a size of theworking pad, an area of the working pad, or a thickness of the workingpad. In certain embodiments, each in vitro analyte sensor includes anelectrical trace and the manufacturing parameter is a resistance of theelectrical trace.

In some embodiments, the biochemical attribute is a level of glucose.

In some embodiments, the first and second subsets are from a sameproduction lot. In some embodiments, the multitude of medical devices isa production lot of the medical devices.

In many embodiments, an analyte monitoring system is provided thatincludes: a sensor control device including: an in vivo analyte sensorand electronics communicatively coupled with the in vivo analyte sensor,the electronics including non-transitory memory, where individualizedcalibration information is stored in the memory, and where theindividualized calibration information is based on a measuredmanufacturing parameter of the in vivo analyte sensor and is specific tothe in vivo analyte sensor.

In some embodiments, the electronics further include wirelesscommunication circuitry and processing circuitry, and the non-transitorymemory has a multitude of instructions stored thereon that, whenexecuted by the processing circuitry, cause the processing circuitry to:determine an analyte level from raw data measured by the in vivo analytesensor and from the individualized calibration information; and outputthe determined analyte level to the wireless communication circuitry fortransmission.

In some embodiments, the electronics further include wirelesscommunication circuitry and processing circuitry, and the non-transitorymemory includes a multitude of instructions stored thereon that, whenexecuted by the processing circuitry, cause the processing circuitry to:output the individualized calibration information to the wirelesscommunication circuitry for transmission; and output raw analyte datacollected by the in vivo analyte sensor to the wireless communicationcircuitry for transmission.

In some embodiments, the sensor control device has a lifespan and isusable for the lifespan without user calibration.

In some embodiments, the sensor control device has a lifespan and isusable for the lifespan without user calibration and without systemcalibration.

In some embodiments, the system further includes: a reader deviceincluding processing circuitry, wireless communication circuitry, andnon-transitory memory including a multitude of instructions that, whenexecuted by the processing circuitry, cause the processing circuitry todetermine an analyte level from raw data measured by the in vivo analytesensor and from the individualized calibration information, the rawanalyte data and individualized communication information being receivedfrom the sensor control device.

In some embodiments, the measured manufacturing parameter is a size of asensing region of the in vivo analyte sensor, and the sensing regionincludes a sensing element, the sensing element being in a well of asensor substrate and/or the sensing element being on or adjacent to amodified area of the sensor substrate having a liquid mobilitycharacteristic different than an adjacent area of the sensor substrate.

In many embodiments, a method of analyte monitoring is provided wherethe method includes: processing raw analyte data, collected with ananalyte sensor, with individualized calibration information to determinean analyte level of a user, where the individualized calibrationinformation is based on a measured manufacturing parameter of theanalyte sensor and is specific to the analyte sensor.

In some embodiments, the analyte sensor is an in vivo analyte sensorthat is a component of a sensor control device that further includesprocessing circuitry, where the processing circuitry of the sensorcontrol device processes the raw analyte data with individualizedcalibration information to determine the analyte level of the user.

In some embodiments, the method further includes collecting raw analytedata from a user with the in vivo analyte sensor prior to processing theraw analyte data.

In some embodiments, the method further includes: wirelesslycommunicating the individualized calibration information to a readerdevice and wirelessly communicating the collected raw analyte data to areader device. In certain embodiments, the reader device includesprocessing circuitry, where the processing circuitry of the readerdevice processes the raw analyte data with individualized calibrationinformation to determine the analyte level of the user.

In some embodiments, the in vivo analyte sensor has a lifespan, and themethod further includes using the in vivo analyte sensor for thelifespan without performing user calibration.

In some embodiments, the in vivo analyte sensor has a lifespan, and themethod further includes using the in vivo analyte sensor for thelifespan without performing user calibration and without performingsystem calibration.

In some embodiments, the analyte sensor is an in vitro analyte sensor.In certain embodiments, the in vitro analyte sensor is a strip-based invitro analyte sensor.

In some embodiments, the measured manufacturing parameter is a size of asensing region of the analyte sensor, and the sensing region includes asensing element, the sensing element being in a well of a sensorsubstrate and/or the sensing element being on or adjacent to a modifiedarea of the sensor substrate having a liquid mobility characteristicdifferent than an adjacent area of the sensor substrate.

In many embodiments, a kit is provided that includes: a first in vivoanalyte sensor of a first sensor control device; first electronics ofthe first sensor control device, the first electronics including a firstnon-transitory memory on which is stored first individualizedcalibration information that is based on a measured manufacturingparameter of the first in vivo analyte sensor and is specific to thefirst in vivo analyte sensor; a second in vivo analyte sensor of asecond sensor control device; and second electronics of the secondsensor control device, the second electronics including a secondnon-transitory memory on which is stored second individualizedcalibration information that is based on a measured manufacturingparameter of the second in vivo analyte sensor and is specific to thesecond in vivo analyte sensor, where the first in vivo analyte sensor,the first electronics, the second in vivo analyte sensor, and the secondelectronics are coupled with each other by a common packaging.

In some embodiments, the first and second in vivo analyte sensors arefrom the same in vivo sensor manufacturing lot.

In some embodiments, the kit further includes: a third in vivo analytesensor of a third sensor control device; and third electronics of thethird sensor control device, the third electronics including a thirdnon-transitory memory on which is stored third individualizedcalibration information that is based on a measured manufacturingparameter of the third in vivo analyte sensor and is specific to thethird in vivo analyte sensor, where the first in vivo analyte sensor,the first electronics, the second in vivo analyte sensor, the secondelectronics, the third in vivo sensor, and the third electronics arecoupled with each other by a common packaging.

In some embodiments, the first, second, and third in vivo analytesensors are from the same in vivo sensor manufacturing lot.

In some embodiments, the measured manufacturing parameter is a size of asensing region of the first in vivo analyte sensor, and the sensingregion includes a sensing element, the sensing element being in a wellof a sensor substrate and/or the sensing element being on or adjacent toa modified area of the sensor substrate having a liquid mobilitycharacteristic different than an adjacent area of the sensor substrate.

In many embodiments, a method of analyte monitoring is provided wherethe method includes: collecting a sample of body fluid from a livingbody on an in vitro strip, the in vitro strip including an in vitroanalyte sensor; inserting the in vitro strip into a meter; anddetermining an analyte level in the sample of body fluid usingindividualized calibration information and a signal received from the invitro analyte sensor, where the individualized calibration informationis based on a measured manufacturing parameter of the in vitro analytesensor and is specific to the in vitro analyte sensor.

In some embodiments, the method further includes manually typing theindividualized calibration information into the meter.

In some embodiments, the method further includes automatically inputtingthe individualized calibration information into the meter.

In some embodiments, the method further includes automatically inputtingthe individualized calibration information into the meter by using anoptical scanner and at least one of the following: a barcode, a datamatrix code, a two-dimensional code, or a three-dimensional code.

In some embodiments, the method further includes automatically inputtingthe individualized calibration information into the meter by using atleast one of the following: an RF tag, a resistive coded trace, a ROMcalibrator, or Bluetooth circuitry.

In some embodiments, the method further includes: obtaining thecalibration information by a second electronic device; and sending thecalibration information to the meter over a Bluetooth connection. Incertain embodiments, the second electronic device is a mobile phone. Incertain embodiments, the calibration information is obtained by use ofan optical scanner or Near Field Communication (NFC) circuitry of thephone.

In some embodiments, the measured manufacturing parameter is a size of asensing region of the in vitro analyte sensor, and the sensing regionincludes a sensing element, the sensing element being in a well of asensor substrate and/or the sensing element being on or adjacent to amodified area of the sensor substrate having a liquid mobilitycharacteristic different than an adjacent area of the sensor substrate.

In many embodiments, a method for individualized medical devicecalibration is provided, where the method includes determining, withprocessing circuitry, individualized calibration information for amedical device using at least a representation of a manufacturingparameter of the medical device.

In some embodiments, the medical device is a first medical device, andthe method further includes determining, with processing circuitry, theindividualized calibration information for the first medical deviceusing at least the representation of the manufacturing parameter for thefirst medical device and a representation of a sensing characteristic ofa second medical device.

In certain embodiments, the method further includes determining, withprocessing circuitry, the representation of the sensing characteristicof the second medical device.

In certain embodiments, the method further includes performing an invitro test on the second medical device and determining, with processingcircuitry, the representation of the sensing characteristic of thesecond medical device from in vitro test data collected from the invitro test.

In certain embodiments, the method further includes obtaining themanufacturing parameter from the first medical device. In certainembodiments, the manufacturing parameter is obtained during or after amanufacturing stage for the first medical device.

In certain embodiments, the first and second medical devices are in vivosensors. In certain embodiments, the first and second medical devicesare in vitro sensors. In certain embodiments, the first and secondmedical devices are in vitro test strips. In certain embodiments, thefirst and second medical devices are adapted to sense a biochemicalattribute.

In certain embodiments, the representation of the manufacturingparameter is a representation of an individualized manufacturingparameter.

In some embodiments, the manufacturing parameter is a size of a sensingregion of the medical device, and the sensing region includes a sensingelement, the sensing element being in a well of a sensor substrateand/or the sensing element being on or adjacent to a modified area ofthe sensor substrate having a liquid mobility characteristic differentthan an adjacent area of the sensor substrate.

In many embodiments, a method of manufacturing is provided, the methodincluding: modifying an area of a surface of a sensor substrate withelectromagnetic radiation to create a modified area; and applying aliquid agent to the surface of the sensor substrate such that the liquidagent comes to rest in a target area on the surface, where the targetarea is determined at least in part by the location of the modifiedarea. The modified area can border the target area.

In some embodiments, the modified area has a ring-like shape. The targetarea can be within an interior of the ring-like shape. In someembodiments, the ring-like shape can have an interior border thatdefines an interior of the ring-like shape, and the target area can bethe interior of the ring-like shape. The ring-line shape can be a regionbetween two concentric circles.

In some embodiments, the target area is round or polygonal. In someembodiments, the target area is not adjacent to the modified area. Insome embodiments, the modified area and the target area are the same.

In some embodiments, the modified area attracts the liquid agent. Inother embodiments, the modified area repels the liquid agent.

In some embodiments, the electromagnetic radiation is laser radiation inthe ultraviolet or visible spectrum. The laser radiation can be pulsedto create the modified area.

In some embodiments, the modified area of the sensor substrate includescarbon.

In some embodiments, the method further includes: focusing a laser onthe surface of the sensor substrate; and activating the laser to modifythe area of the surface of the sensor substrate with laser radiation tocreate the modified area.

In some embodiments, the electromagnetic radiation is laser radiation,and the method further includes: entering a size for the modified areainto a laser marking system; and focusing the laser marking system onthe substrate prior to modifying the area of the surface of the sensorsubstrate with laser radiation. The modified area can be a firstmodified area, and the method can further include: moving either thesubstrate or a portion of the laser marking system; and modifying asecond area of the surface of the sensor substrate with laser radiationto create a second modified area. In some embodiments, the methodincludes transferring the substrate to a liquid agent dispense systemhaving a nozzle; and applying the liquid agent from the nozzle to thesurface of the sensor substrate such that the liquid agent comes to restin the target area on the surface.

In some embodiments, the liquid agent is an electrochemical agent.

In some embodiments, the method further includes drying the liquid agentto form a sensing element in the target area.

In some embodiments, the modified area is at least one of: a bottom of awell in the substrate, a sidewall of a well in the substrate, or an areasurrounding a well in the substrate.

In many embodiments, a method of manufacturing is provided, the methodincluding: creating a well in a sensor substrate; and applying a liquidagent into the well in the sensor substrate such that the liquid agentcomes to rest in the well.

In some embodiments, the well includes a bottom and a sidewall. Theliquid agent can be applied to the bottom of the well.

In some embodiments, the liquid agent is an electrochemical agent. Themethod can further include drying the liquid agent to form a sensingelement in the well. In some embodiments, the well includes a bottom anda sidewall, and the sensing element covers a majority of the bottom. Insome embodiments, the well includes a bottom and a sidewall, and thesensing element covers the entire bottom.

In some embodiments, the well includes a bottom surface that is round,circular, or polygonal.

In some embodiments, the method further includes: aligning a tip of atool with an alignment feature on a surface of the sensor substrate; andforcing the tip of the tool into the substrate to create the well in thesubstrate. In some embodiments, the well is a first well, and the methodfurther includes: moving either the substrate or the tip of the tool;and forcing the tip of the tool into the substrate to create a secondwell in the substrate. In some embodiments, the method further includes:transferring the substrate to a liquid agent dispense system having anozzle, where applying the liquid agent into the well in the sensorsubstrate such that the liquid agent comes to rest in the well includesdispensing a drop of the liquid agent from the nozzle into the well.

In some embodiments, a bottom surface of the well has been modified withelectromagnetic radiation and has a liquid mobility characteristic thatis different from an adjacent surface of the substrate.

In some embodiments, a sidewall surface of the well has been modifiedwith electromagnetic radiation and has a liquid mobility characteristicthat is different from an adjacent surface of the substrate.

In some embodiments, a surface of the substrate surrounding the well hasbeen modified with electromagnetic radiation and has a liquid mobilitycharacteristic that is different from an adjacent surface of thesubstrate.

In many embodiments, an analyte monitoring system is provided, theanalyte monitoring system including: an in vivo analyte sensor includinga substrate and at least one sensing element on the substrate, the atleast one sensing element including an electrochemical agent, where thesensing element is on, adjacent to, or in proximity to a modified areaon a surface of the substrate, the modified area having a liquidmobility characteristic that is different from an area of the surface ofthe substrate adjacent to the modified area.

In some embodiments, the modified area has a ring-like shape. Thesensing element can be within an interior of the ring-like shape. Thering-like shape can have an interior border that defines an interior ofthe ring-like shape, and the sensing element covers the interior of thering-like shape. The ring-line shape can be a region between twoconcentric circles.

In some embodiments, the modified area is round, such as circular orelliptical.

In some embodiments, the sensing element is on the modified area.

In some embodiments, the sensing element is adjacent to the modifiedarea.

In some embodiments, the liquid mobility characteristic is such that theelectrochemical agent in liquid form is relatively more attracted to themodified area than the area of the surface of the substrate adjacent tothe modified area.

In some embodiments, the liquid mobility characteristic is such that theelectrochemical agent in liquid form is relatively more attracted to thearea of the surface of the substrate adjacent to the modified area thanto the modified area.

In some embodiments, the modified area is at least one of a bottom of awell in the substrate, a sidewall of a well in the substrate, or an areasurrounding a well in the substrate.

In some embodiments, the system further includes: electronicscommunicatively coupled with the in vivo analyte sensor, the electronicsincluding non-transitory memory, where individualized calibrationinformation is stored in the memory, where the individualizedcalibration information is based on a measured manufacturing parameterof the in vivo analyte sensor and is specific to the in vivo analytesensor.

In some embodiments, the measured manufacturing parameter isrepresentative, at least in part, of a size of the sensing element.

In some embodiments, the in vivo analyte sensor includes a membrane, andthe measured manufacturing parameter is representative, at least inpart, of a size of the membrane.

In many embodiments, an analyte monitoring system is provided, thesystem including: an in vivo analyte sensor having a substrate and atleast one sensing element on the substrate, the at least one sensingelement including an electrochemical agent, where the sensing element isin a well in a surface of the substrate.

In some embodiments, the well includes a bottom surface. The sensingelement can cover only a portion of the bottom surface of the well, orthe sensing element can cover the entire bottom surface of the well.

In some embodiments, the sensing element has a height that is less thana depth of the well. In some embodiments, the sensing element has aheight that is equal to a depth of the well. In some embodiments, thesensing element has a height that is greater than a depth of the well.

In some embodiments, the well includes a bottom surface that is round orpolygonal.

In some embodiments, a bottom surface of the well has a liquid mobilitycharacteristic that is different from an adjacent surface of thesubstrate.

In some embodiments, the well incudes a bottom surface and a sidewallsurface. In some embodiments, the bottom surface of the well has aliquid mobility characteristic that is different from an adjacentsurface of the substrate. In some embodiments, the sidewall surface ofthe well has a liquid mobility characteristic that is different from anadjacent surface of the substrate. In some embodiments, a surface of thesubstrate surrounding the well has a liquid mobility characteristic thatis different from an adjacent surface of the substrate.

In some embodiments, the system further includes electronicscommunicatively coupled with the in vivo analyte sensor, the electronicsincluding non-transitory memory, where individualized calibrationinformation is stored in the memory, where the individualizedcalibration information is based on a measured manufacturing parameterof the in vivo analyte sensor and is specific to the in vivo analytesensor. In some embodiments, the measured manufacturing parameter isrepresentative, at least in part, of a size of the sensing element. Insome embodiments, the in vivo analyte sensor includes a membrane, andthe measured manufacturing parameter is representative, at least inpart, of a size of the membrane.

APPENDIX: EXAMPLES OF MODELS

The following is a general description of various models that can beused with the calibration embodiments described herein. Those ofordinary skill in the art will recognize the many different ways theseand other models can be implemented in light of the disclosure presentedin this appendix and elsewhere throughout this description.

Random forest models are an ensemble learning method which can constructa multitude of decision trees as samples of the full data and outputtingthe class which is the mean prediction of the individual trees. Eachtree can be created by partitioning the space into smaller regions whereinteractions are more manageable, which can then be partitioned again,e.g., recursive partitioning. The following is an example of a generalrandom forest algorithm:

-   -   1) Start with the single node. Calculate for each partition leaf        c, S=Σ_(c∈leaves(T)) Σ_(i∈C)(y_(i)−m_(c))² where

$m_{c} = {\frac{1}{n_{c}}{\sum}_{i \in C}y_{c}}$

-   -   2) Search over all binary splits of all variables to see which        will reduce S as much as possible. If the largest decrease is        less than a threshold δ or the node contains less than q points        then stop. Otherwise create the two new nodes    -   3) In each new node go back to step 1.

Non-linear regressions are a form of regression analysis modelled by afunction which is a nonlinear combination of the model parameters anddepends on one of more independent variables. Y=ƒ(X, β), where X is avector of p predictors and β is a vector of k parameters. The followingis an example of a general nonlinear regression:

$y_{i} = \frac{\beta_{0} + {\beta_{1}x_{1}}}{1 + {\beta_{2}e^{\beta_{3}x_{3}}}}$

Bayesian regression models are another example. In Bayesian statistics,the posterior distribution is conditional probability of an unknowntreated as a random variable—p(β|X). It is proportional to thelikelihood function which is the probability of the evidence given theparameters. p(X|β) multiplied by a prior belief that the probabilitydistribution function is p(β). An example of a Bayesian linearregression follows:

E[y|β]=Aθ

Where β is a vector of p parameters, A is a known n×p matrix and C isthe variance-covariance dispersion matrix. Then where N is the normaldistribution

y˜N(Aβ,C)

Where A and C are known:

β˜N(μ,C2)

Where μ and C are also known.

All features, elements, components, functions, and steps described withrespect to any embodiment provided herein are intended to be freelycombinable and substitutable with those from any other embodiment. If acertain feature, element, component, function, or step is described withrespect to only one embodiment, then it should be understood that thatfeature, element, component, function, or step can be used with everyother embodiment described herein unless explicitly stated otherwise.This paragraph therefore serves as antecedent basis and written supportfor the introduction of claims, at any time, that combine features,elements, components, functions, and steps from different embodiments,or that substitute features, elements, components, functions, and stepsfrom one embodiment with those of another, even if the followingdescription does not explicitly state, in a particular instance, thatsuch combinations or substitutions are possible. It is explicitlyacknowledged that express recitation of every possible combination andsubstitution is overly burdensome, especially given that thepermissibility of each and every such combination and substitution willbe readily recognized by those of ordinary skill in the art.

In all of the embodiments described herein, electronic devices capableof processing data or information can include processing circuitrycommunicatively coupled with non-transitory memory, where thenon-transitory memory can store one or more computer program or softwareinstructions that, when executed by the processing circuitry, cause theprocessing circuitry to take actions. For every embodiment of a methoddisclosed herein, systems and devices capable of performing thosemethods, or portions thereof, with processing circuitry andnon-transitory memory having one or more instructions stored thereonthat, when executed by the processing circuitry, cause that processingcircuitry to execute one or more steps of the method (or cause theexecution of one or more steps of the method, such as transmission ordisplay of information), are within the scope of the present disclosure.

Computer program or software instructions for carrying out operations inaccordance with the described subject matter may be written in anycombination of one or more programming languages, including an objectoriented programming language such as Java, JavaScript, Smalltalk, C++,C #, Transact-SQL, XML, PHP or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program instructions may execute entirely onthe computing device, partly on the computing device, as a stand-alonesoftware package, partly on a local computing device and partly on aremote computing device or entirely on a remote computing device orserver. In the latter scenario, the remote computing device may beconnected to the local computing device through any type of network,including a local area network (LAN) or a wide area network (WAN), orthe connection may be made to an external computer (for example, throughthe Internet using an Internet Service Provider).

To the extent the embodiments disclosed herein include or operate inassociation with memory, storage, and/or computer readable media, thenthat memory, storage, and/or computer readable media are non-transitory.Accordingly, to the extent that memory, storage, and/or computerreadable media are covered by one or more claims, then that memory,storage, and/or computer readable media is only non-transitory.

As used herein and in the appended claims, the singular forms “a,” “an,”and “the” include plural referents unless the context clearly dictatesotherwise.

While the embodiments are susceptible to various modifications andalternative forms, specific examples thereof have been shown in thedrawings and are herein described in detail. It should be understood,however, that these embodiments are not to be limited to the particularform disclosed, but to the contrary, these embodiments are to cover allmodifications, equivalents, and alternatives falling within the spiritof the disclosure. Furthermore, any features, functions, steps, orelements of the embodiments may be recited in or added to the claims, aswell as negative limitations that define the inventive scope of theclaims by features, functions, steps, or elements that are not withinthat scope.

What is claimed is:
 1. A method for manufacturing an in vivo glucosesensor, comprising: physically associating a unique identifier with eachof a plurality of in vivo glucose sensors, such that each of theplurality of in vivo glucose sensors is uniquely identifiable by theassociated identifier; subjecting a first in vivo glucose sensor of theplurality of in vivo glucose sensors to a first manufacturing stage,wherein the first manufacturing stage includes: reading the identifierphysically associated with the first in vivo glucose sensor; obtaining afirst individualized manufacturing parameter associated with the firstin vivo glucose sensor; and storing, in a log, the first individualizedmanufacturing parameter associated with the first in vivo glucosesensor, an indication of a first date corresponding to the firstmanufacturing stage, and an indication of a first time corresponding tothe first manufacturing stage; subjecting the first in vivo glucosesensor of the plurality of in vivo glucose sensors to a secondmanufacturing stage, wherein the second manufacturing stage includes:reading the identifier physically associated with the first in vivoglucose sensor; obtaining a second individualized manufacturingparameter associated with the first in vivo glucose sensor; and storing,in the log, the second individualized manufacturing parameter associatedwith the first in vivo glucose sensor, an indication of a second datecorresponding to the second manufacturing stage, and an indication of asecond time corresponding to the second manufacturing stage; determiningindividualized calibration information associated with the first in vivoglucose sensor, wherein the individualized calibration information isdetermined based at least in part on at least one of the firstindividualized manufacturing parameter associated with the respective invivo glucose sensor and the second individualized manufacturingparameter associated with the respective in vivo glucose sensor;assigning the first in vivo glucose sensor to a first electronics unit,the first electronics unit having a non-transitory memory; integratingthe first in vivo glucose sensor with the first electronics unit; andpackaging the first in vivo glucose sensor with the first electronicsunit to physically maintain the assigned relationship.
 2. The method ofclaim 1, further comprising transmitting to the first electronic unitthe individualized calibration information associated with the first invivo glucose sensor for storage in the first electronics unit.
 3. Themethod of claim 2, wherein transmitting occurs prior to packaging. 4.The method of claim 2, where transmitting the individualized calibrationinformation associated with the first in vivo glucose sensor compriseswirelessly transmitting the individualized calibration informationassociated with the first in vivo glucose sensor.
 5. The method of claim4, wherein packaging occurs prior to transmitting.
 6. The method ofclaim 1, further comprising subjecting each additional in vivo glucosesensor of the plurality of in vivo glucose sensors to the firstmanufacturing stage.
 7. The method of claim 6, wherein the firstmanufacturing stage comprises, for each of the additional in vivoglucose sensors: reading the identifier physically associated with therespective in vivo glucose sensor; and obtaining a first respectiveindividualized manufacturing parameter associated with the respective invivo glucose sensor; and storing, in the log, the first respectiveindividualized manufacturing parameter associated with the respective invivo glucose sensor, an indication of a first respective datecorresponding to the first manufacturing stage, and an indication of afirst respective time corresponding to the first manufacturing stage. 8.The method of claim 7, further comprising subjecting each of theadditional in vivo glucose sensors of the plurality of in vivo glucosesensors to the second manufacturing stage.
 9. The method of claim 8,wherein the second manufacturing stage comprises, for each of theadditional in vivo glucose sensors: reading the identifier physicallyassociated with the respective in vivo glucose sensor; and obtaining asecond respective individualized manufacturing parameter associated withthe respective in vivo glucose sensor; and storing, in the log, thesecond respective individualized manufacturing parameter associated withthe respective in vivo glucose sensor, an indication of a secondrespective date corresponding to the second manufacturing stage, and anindication of a second respective time corresponding to the secondmanufacturing stage.
 10. The method of claim 9, further comprising, foreach of the additional in vivo glucose sensors: determiningindividualized calibration information associated with the respective invivo glucose sensor, wherein the individualized calibration informationis determined based at least in part on at least one of the firstrespective individualized manufacturing parameter associated with therespective in vivo glucose sensor and the second respectiveindividualized manufacturing parameter associated with the respective invivo glucose sensor; assigning the respective in vivo glucose sensor toa respective electronics unit, the respective electronics unit having anon-transitory memory; integrating the respective in vivo glucose sensorwith the respective electronics unit; and packaging the respective invivo glucose sensor with the respective electronics unit to physicallymaintain the assigned relationship.
 11. The method of claim 10, furthercomprising, for each of the additional in vivo glucose sensors,transmitting to the respective electronic unit the individualizedcalibration information associated with the respective in vivo glucosesensor for storage in the respective electronics unit.
 12. The method ofclaim 11, wherein transmitting occurs prior to packaging.
 13. The methodof claim 11, where transmitting the individualized calibrationinformation associated with the first in vivo glucose sensor compriseswirelessly transmitting the individualized calibration informationassociated with the first in vivo glucose sensor.
 14. The method ofclaim 13, wherein packaging occurs prior to transmitting.
 15. The methodof claim 1, further comprising subjecting a baseline subset of theplurality of in vivo glucose sensors to in vitro testing to provide invitro test data.
 16. The method of claim 15, wherein determining theindividualized calibration information is further based at least in parton the in vitro test data.
 17. The method of claim 1, wherein theidentifier comprises a Near Field Communication (NFC) element.
 18. Themethod of claim 1, wherein the identifier comprises a printedtwo-dimensional code.
 19. The method of claim 1, wherein the identifiercomprises a barcode.
 20. The method of claim 1, wherein the identifiercomprises optical character recognizable (OCR) text.
 21. The method ofclaim 1, wherein the identifier comprises a resistive code.
 22. Themethod of claim 1, wherein the first individualized manufacturingparameter obtained at the first manufacturing stage comprises aquantitative manufacturing parameter.
 23. The method of claim 1, whereinthe first manufacturing parameter obtained at the first manufacturingstage comprises a individualized qualitative manufacturing parameter.24. The method of claim 1, wherein the first manufacturing stage furtherincludes storing the first manufacturing stage in the log.
 25. Themethod of claim 1, wherein the first individualized manufacturingparameter obtained at the first manufacturing stage comprises a lengthof time the first in vivo glucose sensor spent at the firstmanufacturing stage.
 26. The method of claim 1, wherein the firstindividualized manufacturing parameter obtained at the firstmanufacturing stage comprises a size or dimensional measurementassociated with the first in vivo glucose sensor.
 27. The method ofclaim 1, wherein the first individualized manufacturing parameterobtained at the first manufacturing stage comprises a chemicalcomposition or chemical concentration associated with the first in vivoglucose sensor.
 28. The method of claim 1, wherein the firstindividualized manufacturing parameter obtained at the firstmanufacturing stage comprises an electrical characteristic associatedwith the first in vivo glucose sensor.
 29. The method of claim 1,wherein the first individualized manufacturing parameter obtained at thefirst manufacturing stage comprises an environmental condition.
 30. Themethod of claim 1, wherein each of the first plurality of medicaldevices comprises a sensing region comprising a sensing element, thesensing element being on a modified area of a sensor substrate having aliquid mobility characteristic different than an adjacent area of thesensor substrate.